How does one encode / interpret the value of this AVP / IE was the question I set out to answer.
TS 29.274 says:
For the encoding of this information element see 3GPP TS 32.298
TS 32.298 says:
The functional requirements for the Charging Characteristics as well as the profile and behaviour bits are further defined in normative Annex A of TS 32.251
TS 32.251 Annex A says:
The Charging Characteristics parameter consists of a string of 16 bits designated as Behaviours (B), freely defined by Operators, as shown in TS 32.298 [51]. Each bit corresponds to a specific charging behaviour which is defined on a per operator basis, configured within the PCN and pointed when bit is set to “1” value.
After a few circular references I found this is imported from 32.298.
Finally we find some solid answers hidden away in TS 132 215, under the Charging Characteristics Profile index.
Charging Characteristics consists of a string of 16 bits designated as Profile (P) and Behaviour (B), shown in Figure 4. The first four bits (P) shall be used to select different charging trigger profiles, where each profile consists of the following trigger sets:
S-CDR: activate/deactivate CDRs, time limit, volume limit, maximum number of charging conditions, tariff times;
G-CDR: same as SGSN, plus maximum number of SGSN changes;
M-CDR: activate/deactivate CDRs, time limit, and maximum number of mobility changes;
SMS-MO-CDR: activate/deactivate CDRs;
SMS-MT-CDR: active/deactivate CDRs.
The Charging Characteristics field allows the operator to apply different kind of charging methods in the CDRs. A subscriber may have Charging Characteristics assigned to his subscription. These characteristics can be supplied by the HLR to the SGSN as part of the subscription information, and, upon activation of a PDP context, the SGSN forwards the charging characteristics to the GGSN on the Gn / Gp reference point according to the rules specified in Annex A of TS 32.251 [11].
This information can be used by the GSNs to activate CDR generation and control the closure of the CDR or the traffic volume containers (see clause 5.1.2.2.23) and is included in CDRs transmitted to nodes handling the CDRs via the Ga reference point. It can also be used in nodes handling the CDRs (e.g., the CGF or the billing system) to influence the CDR processing priority and routing.
These functions are accomplished by specifying the charging characteristics as sets of charging profiles and the expected behaviour associated with each profile.
The interpretations of the profiles and their associated behaviours can be different for each PLMN operator and are not subject to standardisation. In the present document only the charging characteristic formats and selection modes are specified.
The functional requirements for the Charging Characteristics as well as the profile and behaviour bits are further defined in normative Annex A of TS 32.251 [11], including the definitions of the trigger profiles associated with each CDR type.
The format of charging characteristics field is depicted in Figure 4. Px (x =0..3) refers to the Charging Characteristics Profile index. Bits classified with a “B” may be used by the operator for non-standardised behaviour (see Annex A of TS 32.251 [11]).
Right, well hopefully next time someone goes looking for this info you’ll find it a bit more easily than I did!
The S8 Home Routing approach for LTE Roaming works really well, as more and more operators are switching off their legacy circuit switched 2G/3G networks and shifting to LTE & VoLTE for roaming, we’re seeing more an more S8-HR deployments.
When LTE was being standardised in 2008, Local Breakout (LBO) and S8 Home Routing were both considered options for how roaming may look. Fast forward to today, and S8 Home routing is the only way roaming is done for modern deployments.
In light of this, there are some “best practices” in an “all S8 Home Routed” world, we’ve developed, that I thought I’d share.
The Basics
When roaming, the SGW in the Visited Network, sends user traffic back to the PGW in the Home Network.
This means Online/Offline charging, IMS, PCRF, etc, is all done in the Home PLMN. As long as data packets can get from the SGW in the Visited PLMN to the PGW in the Home PLMN, and authentication flows from the Visited MME to the HSS in the Home PLMN, you’re golden.
The Constraints
Of course real networks don’t look as simple as this, in reality a roaming scenario for a visited network has a lot more nodes, which need to be
Building Distributed Packet Core & IMS
Virtualization (VNF / CNF) has led operators away from “big iron” hardware for Packet Core & IMS nodes, towards software based solutions, which in turn offer a lot more flexibility.
Best practice for design of User Plane is to keep the the latency down, by bringing the user plane closer to the user (the idea of “Edge” UPFs in 5GC is a great example of this), and the move away from “big iron” in central locations for SGW and PGW nodes has been the trend for the past decade.
So to achieve these goals in the networks we build, we geographically distribute the core network.
This means we’ve got quite a few S-GW, P-GW, MME & HSS instances across the network. There’s some real advantages to this approach:
From a redundancy perspective this allows us to “spread the load” and build far more resilient networks. A network with 20 smaller HSS instances spread around the country, is far more resilient than 2 massive ones, regardless of how many power feeds or redundant disks it may have.
This allows us to be more resource efficient. MNOs have always provisioned excess capacity to cater for the loss of a node. If we have 2 MMEs serving a country, then each node has to have at least 50% capacity free, so if one MME were to fail, the other MME could handle the additional load it from it’s dead friend. This is costly for resources. Having 20 MMEs means each MME has to have 5% capacity free, to handle the loss of one MME in the pool.
It also forces our infrastructure teams to manage infrastructure “as cattle” rather than pets. These boxes don’t get names or lovingly crafted, they’re automatically spun up and destroyed without thinking about it.
For security, we only use internal IP addresses for the nodes in our packet core, this provides another layer of protection for the “crown jewels” of our network, so no one messing with BGP filtering can accidentally open the flood gates to our core, as one US operator learned leaving a GGSN open to the world leading to the private information for 100 million customers being leaked.
What this all adds to, is of course, the end user experience. For the end subscriber / customer, they get a better experience thanks to the reduced latency the connection provides, better uptime and faster call setup / SMS delivery, and less cost to deliver services.
I love this approach and could prothletise about it all day, but in a roaming context this presents some challenges.
The distributed networks we build are in a constant state of flux, new capacity is being provisioned in some areas, nodes things decommissioned in others, and our our core nodes are only reachable on internal IPs, so wouldn’t be reachable by roaming networks.
Our Distributed-Core Roaming Solution
To resolve this we’ve taken a novel approach, we’ve deployed a pair of S-GWs we call the “Roaming SGWs”, and a pair of P-GWs we call the “Roaming PGWs”, these do have public IPs, and are dedicated for use only by roaming traffic.
We really like this approach for a few reasons:
It allows us to be really flexible do what we want inside the network, without impacting roaming customers or operators who use our network for roaming. All the benefits I described from the distributed architectures can still be realised.
From a security standpoint, only these SGW/PGW pairs have public IPs, all the others are on internal IPs. This good for security – Our core network is the ‘crown jewels’ of the network and we only expose an edge to other providers. Even though IPX networks are supposed to be secure, one of the largest IPX providers had their systems breached for 5 years before it was detected, so being almost as distrustful of IPX traffic as Internet traffic is a good thing. This allows us to put these PGWs / SGWs at the “edge” of our network, and keep all our MMEs, as well as our on-net PGW and SGWs, on internal IPs, safe and secure inside our network.
For charging on the SGWs, we only need to worry about collecting CDRs from one set of SGWs (to go into the TAP files we use to bill the other operators), rather than running around hoovering up SGW CDRs from large numbers of Serving Gateways, which may get blown away and replaced without warning.
Of course, there is a latency angle to this, for international roaming, the traffic has to cross the sea / international borders to get to us. By putting it at the edge we’re seeing increased MOS on our calls, as the traffic is as close to the edge of the network as can be.
Caveat: Increased S11 Latency on Core Network sites over Satellite
This is probably not relevant to most operators, but some of our core network sites are fed only by satellite, and the move to this architecture shifted something: Rather than having latency on the S8 interface from the SGW to the PGW due to the satellite hop, we’ve got latency between the MME and the SGW due to the satellite hop.
It just shifts where in the chain the latency lies, but it did lead to us having to boost some timers in the MME and out of sequence deliver detection, on what had always been an internal interface previously.
Evolution to 5G Standalone Roaming
This approach aligns to the Home Routed options for 5G-SA roaming; UPF chaining means that the roaming traffic can still be routed, as seems to be the way the industry is going.
SA roaming is in its infancy, without widely deployed SA networks, we’re not going to see common roaming using SA for a good long while, but I’ll be curious to see if this approach becomes the de facto standard going forward.
Where to from here?
We’re pretty happy with this approach in the networks we’ve been building.
So far it’s made IREG testing easier as we’ve got two fixed points the IPX needs to hit (The DRAs and the SGWs) rather than a wide range of networks.
Operators with a vast number of APNs they need to drop into different VRFs may have to do some traffic engineering here – Our operations are generally pretty flat, but I can see where this may present some challenges for established operators shifting their traffic.
I’d be keen to hear if other operators are taking this approach and if they’ve run into any issues, or any issues others can see in this, feel free to drop a comment below.
Having rated CDRs in CGrateS is great, but in reality, you probably want to get them into a billing system, CSV file, S3 bucket, CRM, invoice, Grafana, SQL table, etc, etc.
The Event Exporter Service (EES (previously called CDRe)) handles exporting CDRs from CGrateS.
Like everything in CGrateS, it’s highly configurable, and, again, like everything in CGrateS, supports every combination of services you can think of, plus a stack you haven’t thought of.
CDRs can be exported one of two ways, in real time, as the CDR is generated (online), or after the fact, exporting from the database containing the CDRs (offline).
Exporting in realtime (online) is a great option if you don’t want (or need) to store the CDRs in CGrateS; if you’re just using CGrateS to rate calls and spit them into a seperate system, this is a fantastic option, as it allows your CGrateS instances to remain light and not get clogged up with lots of old CDRs – That said, of course you can export the CDRs in realtime and still store them in CGrateS, that’s also a totally valid approach as well.
The more traditional approach is offline CDR export, where periodically or when an event is triggered, you scrape up a pile of CDRs and send them to your external systems.
For both options, we’ll need to define at least one exporter in our cgrates.json config file. For this example we’ll define a HTTP POST that we will trigger for realtime (online) CDR exporting, and a CSV file we dump to periodically when called from the API.
So first things first, we enable the EES module in the config:
"ees": {
"enabled": true,
"exporters": [
]
}
We’ll start with defining one exporter, named CSVExporter, that will output files to a folder named “testCSV” in the /tmp/ directory, but you can plonk these files wherever you like:
We’ve got a lot of different types of export available to us, but type *file_csv is the easiest, so that’s where we’ll start.
Setting synchronous to true will mean we’ll only run one export job at a time, but it also means we’ll get back the result via the API, which will allow us to keep track of the ID of the last record we updated, so we don’t export the same record multiple times, more on this later.
Flags allows us to, if we wanted, bounce the event through AttributeS, for example, by adding *attributes to the flags, but in this case, it’s just logging to syslog.
Of course, just enabling ees won’t actually send calls to it, we’ll need to add “ees_conns“: [“*localhost”], to “apiers”: and “cdrs” so they know to bounce the events through it:
If you’ve already got CDRs on your system from our previous tutorial, fantastic, but if not, let’s get up and running with a quick and dirty script to define some destinations, a charger, an account balance and then use some of the balance to generate a CDR:
import cgrateshttpapi
import pprint
import uuid
import datetime
now = datetime.datetime.now()
CGRateS_Obj = cgrateshttpapi.CGRateS('localhost', 2080)
#Define Destinations
CGRateS_Obj.SendData({'method':'ApierV2.SetTPDestination','params':[{"TPid":'cgrates.org',"ID":"Dest_AU_Mobile","Prefixes":["614"]}]})
#Load TariffPlan we just defined from StorDB to DataDB
CGRateS_Obj.SendData({"method":"APIerSv1.LoadTariffPlanFromStorDb","params":[{"TPid":'cgrates.org',"DryRun":False,"Validate":True,"APIOpts":None,"Caching":None}],"id":0})
#Define default Charger
print(CGRateS_Obj.SendData({"method": "APIerSv1.SetChargerProfile","params": [{"Tenant": "cgrates.org","ID": "DEFAULT",'FilterIDs': [],'AttributeIDs' : ['*none'],'Weight': 0,}]}))
account = "Nick_Test_123"
#Add a balance to the account with type *sms with 100 sms events
pprint.pprint(CGRateS_Obj.SendData({"method": "ApierV1.SetBalance","params": [{"Tenant": "cgrates.org","Account": account,"BalanceType": "*sms","DestinationIDs": 'Dest_NZ_Mobile;Dest_AU_Mobile',"Categories": "*any","Balance": {"ID": "100_SMS_Bundle_AU_NZ_Mobile","Value": 100,"Weight": 25}}]}))
#Process CDR Event for a single SMS
pprint.pprint(CGRateS_Obj.SendData({"method": "CDRsV2.ProcessExternalCDR","params": [{"OriginID": str(uuid.uuid1()),"ToR": "*sms","RequestType": "*pseudoprepaid","AnswerTime": now.strftime("%Y-%m-%d %H:%M:%S"),"SetupTime": now.strftime("%Y-%m-%d %H:%M:%S"),"Tenant": "cgrates.org","Account": account,"Destination" : "61412345678","Usage": "1",}]}))
Right, with that out of the way, we should now have something in our CDRs table, a quick SQL query confirms this is the case:
So, as you may have guessed, we’ve called the ExportCDRs API endpoint, we’ve specified which ExporterIDs we want to reference (these link back to the objects in the config, and the one we have defined currently is named CSVExporter).
Setting Verbose: True means that CGrateS gives us back a lot of info from the API call, here’s what we get back:
Now that looks pretty positive, we got 12 events of SMS usage exported, which we can see in the file /tmp/testCSV/CSVExporter_21e9bc2.csv – and if we cat out the file, yeap, there’s all the CDRs.
But it’s a bit of a mess, there’s a lot of fields in there, so let’s adjust what goes into the CSV.
Let’s start by filtering what goes into the exporter, to only give us SMS events, of course you could adjust the filters here to target exporting only the records you want, based on anything you can define with Filters (and there’s a lot you can define with filters).
Now we’re only exporting SMS records, so let’s clean up the output of the CSV to just give us the data we want, which is the CDR ID, time, account, destination and usage.
Now after a restart of CGrateS, our exports look like this:
Stunning, truly beautiful, look at that output!
Right, well you may at this point have noticed a problem if you’ve run this more than once. The problem is that is every time we run this, we get all the CDRs since the beginning of time.
But where filtering by date/time falls down, is that if an offline CDR of a call on Monday, only got ingested on Tuesday, it would be missed by the export.
But, setting Verbose: True on the ExportCDRs API call gives us a handy trick, we’ve been told what the highest ID in the CDRs table we just exported in the response from the API in LastExpOrderID field.
If we jump over to the SQL database we use for StorDB, we can see that 33 is the ID of the highest CDR in the system.
So let’s try something, let’s run the exporter again, but this time let’s get all the CDRs where the ID is higher than 33:
#Process CDR Event for a single SMS
pprint.pprint(CGRateS_Obj.SendData({"method": "CDRsV2.ProcessExternalCDR","params": [{"OriginID": str(uuid.uuid1()),"ToR": "*sms","RequestType": "*pseudoprepaid","AnswerTime": now.strftime("%Y-%m-%d %H:%M:%S"),"SetupTime": now.strftime("%Y-%m-%d %H:%M:%S"),"Tenant": "cgrates.org","Account": account,"Destination" : "61412345678","Usage": "1",}]}))
#Trigger export where the OrderID is above 33
result = CGRateS_Obj.SendData({"method":"APIerSv1.ExportCDRs","params":[
{"ExporterIDs": ["CSVExporter"],
"Verbose" : True,
"ExtraArgs" : {
"OrderIDStart" : int(33),
},
"Accounts" : [account]}
]})
pprint.pprint(result)
Boom, now if we have a look at the output we can see the export covered two records, and the last ID was 35.
So as long as we keep track of the LastExpOrderID value, and feed that as in input every time we run ExportCDRs, we can ensure we never miss a CDR, and never get the same CDR twice.
I got an email the other day asking a simple question:
How do I know if a subscriber is VoLTE roaming or not when they send an SMS to charge for it?
My immediate reaction was to look at the SIP headers, P-Access-Network-Info will tell you where the subscriber is located, end of.
Right?
Well not quite, this will tell the SMSc the location of the subscriber sending the SMS. If the PLMN in the P-Access-Network-Info != the home PLMN, the sub is roaming.
But does this information get passed to the OCS / OFCS?
The SMSc uses “Event based charging” to perform credit control, so let’s have a look at what AVPs are present in the Credit Control Request from the SMSc:
Hmm, the SMS-Information AVP (2000) contains a bunch of information about the SMS being sent, but I don’t see anything about the location of the sender in there.
Originator-Interface is just set to “SIP”, of course in a 2G/3G roaming scenario the Originator-SCCP-Address would be that of the Visited PLMN, but for us it is our SCCP address.
Maybe the standard allows for an additional optional AVP in the SMS-Information-AVP we’re missing? Let’s check TS 32.299:
Nope.
So how to deal with this?
While the standards aren’t totally clear on this, we added an IMS-Info AVP and inside that populated the Access-Network-Information directly from the SIP header, and then picked that off inside our OCS in order to apply the correct rules.
Android, being open source, allows us to see how this logic works, and it’s important for operators to understand this logic, as it’s what dictates the behavior in many scenarios.
It’s important to note that I’m not covering Apple here, this information is not publicly available to share for iOS devices, so I won’t be sharing anything on this – Apple has their own ecosystem to handle emergency calling, if you’re from an operator and reading this, I’d suggest getting in touch with your Apple account manager to discuss it, they’re always great to work with.
The Android Open Source Project has an “emergency number database”. This database has each of the emergency phone numbers and the corresponding service, for each country.
This file can be read at packages/services/Telephony/ecc/input/eccdata.txt on a phone with engineering mode.
Let’s take a look what’s in mainline Android for Australia:
In our last post we looked at Actions and ActionPlans, and one of the really funky things we can do is setting ActionPlans to trigger on a time schedule or setting ActionTriggers to trigger on an event.
We’re going to build on the examples we had on the last post, so we’ll assume your code is up to the point where we’ve added a Signup Bonus to an account, using an ActionPlan we assigned when creating the account.
In this post, we’re going to create an action that charges $6, called “Action_Monthly_Charge“, and tie it to an ActionPlan called “ActionPlan_Monthly_Charge“, but to demo how this works rather than charging this Monthly, we’re going to charge it every minute.
Then with our balances ticking down, we’ll set up an ActionTrigger to trigger when the balance drops below $95, and alert us.
Defining the Monthly Charge Action
The Action for the Monthly charge will look much like the other actions we’ve defined, except the Identifier is *debitso we know we’re deducting from the balance, and we’ll log to the CDRs table too:
Next we’ll need to wrap this up into an ActionPlan, this is where some of the magic happens. Inside the action plan we can set a once off time, or a recurring time, kinda like Cron.
We’re setting the time to *every_minute so things will happen quickly while we watch, this action will get triggered every 60 seconds. In real life of course, for a Monthly charge, we’d want to trigger this Action monthly, so we’d set this value to *monthly. If we wanted this to charge on the 2nd of the month we’d set the MonthDays to “2”, etc, etc.
If you think the accounts will start getting debited every 60 seconds after applying this, you’d be wrong, we need to associate this ActionPlan with an Account first, this is how we control which accounts get which ActionPlans tied to them, to do this we’ll use the SetAccout API again we’ve been using to create accounts:
Well, for starters the ActionPlan named “ActionPlan_Signup_Bonus” is going to be triggered, as in the ActionPlan it’s Timing is set to *asap, so CGrateS will apply the corresponding Action (“Action_Add_Signup_Bonus“) right away, which will credit the account $99.
But a minute after that, we’ll trigger the ActionPlan named “ActionPlan_Monthly_Charge”, as the timing for this is set to *every_minute, when the Action “Action_Monthly_Charge” is triggered, it’s going to be deducting $6 from the balance.
We can check this by using the GetAccount API:
# Get Account Info
pprint.pprint(CGRateS_Obj.SendData({'method': 'ApierV2.GetAccount', 'params': [
{"Tenant": "cgrates.org", "Account": str(Account)}]}))
You should see a balance of $99 to start with, and then after 60 seconds, it should be down to $93, and so on.
Triggering Actions based on Balances with ActionTriggers
Okay, so we’ve set up recurring charges, now let’s get notified if the balance drops below $95, we’ll start, like we have before, with defining an Action, this will log to the CDRs table, HTTP post and write to syslog:
Now we’ll define an ActionTrigger to check if the balance is below $95 and trigger our newly created Action (“Action_HTTP_Notify_95“) when that condition is met:
We’ve defined the ThresholdType of *min_balance, but we could equally set this to ThresholdType to *max_balance, *balance_expired or trigger when a certain Counter has been triggered enough times.
Adding an ActionTrigger to an Account
Again, like the ActionPlan we created before, before the ActionTrigger we just created will be used, we need to associate it with an Account, for this we’ll use the AddAccountActionTriggers API, specify the Account and the ActionTriggerID for the ActionTrigger we just created.
If we run this all together, creating the account with the “ActionPlan_Signup_Bonus” will give the account a $99 Balance. But after 60 seconds, “ActionPlan_Monthly_Charge” will kick in, and every 60 seconds after that, at which point the balance will get to below $95 when CGrateS will trigger the ActionTrigger “ActionTrigger_95_Remaining” and get the HTTP POST to the HTTP endpoint and log entry:
We can check on this using the ApierV2.GetAccount method, where we’ll see the ActionTrigger we just defined.
Checking out the LastExecutionTime we can see if the ActionTrigger been triggered or not.
So using this technique, we can notify a customer when they’ve used a certain amount of their balance, but we can lock out Accounts who have spent more than their allocated spend limit by setting an Action that suspends the Account once it reaches a certain level. We notify customers when balance expires, or if a certain number of counters has been triggered.
In our last post we added a series of different balances to an account, these were actions we took via the API specifically to add a balance.
But there’s a lot more actions we may want to do beyond just adding balance.
CGrateS has the concept of “Actions” which are, as the name suggests, things we want to do to the system.
Some example Actions would be:
Adding / Deducting / Resetting a balance
Adding a CDR log
Enable/Disable an account
Sending HTTP POST request or email notification
Deleting / suspending account
Transferring balances
We can run these actions on a timed basis, or when an event is triggered, and group Actions together to run multiple actions via an ActionTrigger, this means we can trigger these Actions, not just by sending an API request, but based on the state of the subscriber / account.
Let’s look at some examples,
We can define an Action named “Action_Monthly_Fee” to debit $12 from the monetary balance of an account, and add a CDR with the name “Monthly Account Fee” when it does so. We can use ActionTriggers to run this every month on the account automatically.
We can define an Action named “Usage_Warning_10GB” to send an email to the Account owner to inform them they’ve used 10GB of usage, and use ActionTriggers to send this when the customer has used 10GB of their *data balance.
Let’s start basic; to sweeten the deal for new Accounts, we’ll give them $99 of balance to use in the first month they have the service. Rather than hitting the AddBalance API, we’ll define an Action named “Action_Add_Signup_Bonus” to credit $99 of monetary balance to an account.
If you go back to our last post, you should know what we’d need to do to add this balance manually with the AddBalance API, but let’s look at how we can create the same balance add functionality using Actions:
#Add a Signup Bonus of $99 to the account with type *monetary expiring a month after it's added
Action_Signup_Bonus = {
"id": "0",
"method": "ApierV1.SetActions",
"params": [
{
"ActionsId": "Action_Add_Signup_Bonus",
"Actions": [
{
"Identifier": "*topup","BalanceId": "Balance_Signup_Bonus",
"BalanceUuid": "",
"BalanceType": "*monetary",
"Directions": "*out",
"Units": 99,
"ExpiryTime": "*month",
"Filter": "",
"TimingTags": "",
"DestinationIds": "",
"RatingSubject": "",
"Categories": "",
"SharedGroups": "",
"BalanceWeight": 1200,
"ExtraParameters": "",
"BalanceBlocker": "false",
"BalanceDisabled": "false",
"Weight": 10
}
]}]}
pprint.pprint(CGRateS_Obj.SendData(Action_Signup_Bonus))
Alright, this should look pretty familiar if you’ve just come from Account Balances. You’ll notice we’re no longer calling, SetBalance, we’re now calling SetActions, to create the ActionsId with the name “Action_Add_Signup_Bonus“. In “Action_Add_Signup_Bonus” we’ve got an actions we’ll do when “Action_Add_Signup_Bonus” is called. We can define multiple actions, but for now we’ve only got one action defined, which has the Identifier (which defines what the action does) set to *topup to add balance. As you probably guessed, we’re triggering a top up, and setting the BalanceId, BalanceType, Units, ExpiryTime and BalanceWeight just as we would using SetBalance to add a balance.
So how do we use the Action we just created? Well, there’s a lot of options, but let’s start with the most basic – Via the API:
Boom, now we’ll get a CDR created when the Action is triggered.
But let’s push this a bit more and add some more steps in the Action:
As well as adding balance and putting in a CDR to record what we did, let’s also send a notification to our customer via an HTTP API (BYO customer push notification system) and log to Syslog what’s going on.
So what have we done here? We’ve made an ActionPlan named “Action_Add_Signup_Bonus”, which, when associated with an account, will run the Action “Action_Add_Signup_Bonus” as soon as it’s tied to the account, thanks to the Time “*asap“.
Now if we create or update an Account using the SetAccount method, we can set the ActionPlanIds to reference our “ActionPlan_Signup_Bonus” and it’ll be triggered straight away.
Now if we were to run a GetAccount API call, we’ll see the Account balance assigned that was created by the action Action_Add_Signup_Bonus which was triggered by ActionPlan assigned to the account:
But here’s where it gets interesting, in the ActionPlan we just defined the Time was set to “*asap“, which means the Action is triggered as soon as it was assigned to the account, but if we set the Time value to “*monthly“, the Action would get triggered every month, or *every_minute to trigger every minute, or *month_end to trigger at the end of every month.
I’m trying to keep these posts shorter as there’s a lot to cover. Stick around for our next post, we’ll look at some more ActionTriggers to keep decreasing the balance of the account, and setting up ActionTriggers to send a notification to the customer to tell them when their balance is getting low, or any other event based Action you can think of!
For example, an American visiting the UK, would have 911 on the Emergency Calling Codes list on their SIM card, but in the UK they dial 999 to reach emergency services.
There’s two angles to this, the first is if a roamer dials the emergency calling code of their home country, the other is if they dial the emergency calling code of the country they are in.
Let’s look at the first scenario, where the roamer dials the emergency calling code of their home country.
If our American in the UK abroad dials 911, that number is on the ECC list on the SIM, it’s still flagged as an emergency call, and just goes out with the standard urn:service:sos URN – The network never sees 911 or 999, just that it’s an SOS call that goes to the PSAP.
In this scenario, the fact the dialled number is not passed to the network is actually a positive, we get the intent that the user wants to reach emergency services, and route based on this.
But what if our American friend in need dials 999? That’s the correct number for the end user to dial in the UK after all, but if that’s not in their ECC list on the SIM / device, it’d go through as a regular call right?
If the call does not get flagged as an emergency call on the UE this has its own set of complications and considerations:
S8-Home Routing for VoLTE means that as the UE doesn’t know this is an emergency call, the call will get routed back to the home network. This means the call doesn’t go to the E-CSCF in the visited network, and would probably just get a message saying the number they’ve dialed is unavailable, this would be exactly as if they dialed 999 at home in the US.
But we have a fix for this! On each MME we can set a list of emergency numbers, which would allow our Britt’s phone to know on this network, what the emergency calling codes are, and route the 999 call to the local PSAP, rather than home routing it.
This information is jammed into the Emergency Number List IE in the NAS Attach Accept body.
This means our American visitor in the UK, would know about 999 from the ECC list configured in the roaming operator’s MME.
The purpose of this information element is to encode emergency number(s) for use within the country where the IE is received.
3GPP TS 24.008: 10.5.3.13 – Emergency Number List
Where this becomes more problematic is unauthenticated emergency calling.
For example, a our American visiting the UK, that is not roaming dials 999.
We’ll assume the UK and US operator don’t have a VoLTE roaming agreement because they’ve been kicking the can down the road when it comes to VoLTE roaming… This is super common scenario – last numbers I saw on this were last year with ~50 bilateral VoLTE agreements in place worldwide.
Because the phone is not attached to a local MME, the handset does not know that 999 is an emergency calling code (because it’s not on the SIM), after all, the only way it can get the Emergency Number List is from an MME, and not having been attached to an MME, means the phone does not have the ECC list for the country, so the the handset does not begin the emergency attach procedure to make the call.
Common sense prevails here, on the majority of phones and the majority of SIM profiles, codes like 112 or 911 are treated as emergency calls, but more obscure numbers, such as dialing 999 in the UK or 10111 for South African Police on a handset with US firmware, are not guaranteed to work. Generally dialing the Emergency Calling code in the home network would get you through to some emergency services (although as we talked about in the last post, this might get you routed to the wrong agency in countries where each agency has their own number).
A better way forward?
These days I don’t dial much (apart from if I’m making adjustments on the Step-by-Step exchange), when I call people I do it from contacts, hyperlinks, etc.
There is mountains of research to suggest that asking people to remember codes and phone numbers, is a struggle. A tourist who finds themselves in Tunisia in need of assistance, is unlikely to remember that it’s 190 for an Ambulance, and 198 for Fire.
Perhaps the ECC list on a phone should populate a page of icons from the emergency page on the phone, with the universal icon for each agency, that sends to the URN for that service type?
Countries with a single PSAP could have the URNs for each service type routed to the same place, while countries with seperated PSAPs for each service type, can route accordingly.
Likewise if a country does have a centralised PSAP for all call types, knowing the type that is selected would be useful, for example if the user has pressed fire and is not responsive when the call is answered, the best unit to dispatch would probably be a fire engine.
Even before 5G was released, the arms race to claim the “fastest” speeds on LTE, NSA and SA networks has continued, with pretty much every operator claiming a “first” or “fastest”.
I myself have the fastest 5G network available* but I thought I’d look at how big the values are we can put in for speed, these are the Maximum Bitrate Values (like AMBR) we can set on an APN/DNN, or on a Charging Rule.
*Measurement is of the fastest 5G network in an eastward facing office, operated by a person named Nick, in a town in Australia. Other networks operated by people other than those named Nick in eastward facing office outside of Australia were not compared.
The answer for Release 8 LTE is 4294967294 bytes per second, aka 4295 Mbps 4.295 Gbps.
Not bad, but why this number?
The Max-Requested-Bandwidth-DL AVP tells the PGW the max throughput allowed in bits per second. It’s a Unsigned32 so max value is 4294967294, hence the value.
But come release 15 some bright spark thought we may in the not to distant future break this barrier, so how do we go above this?
The answer was to bolt on another AVP – the “Extended-Max-Requested-BW-DL” AVP ( 554 ) was introduced, you might think that means the max speed now becomes 2x 4.295 Gbps but that’s not quite right – The units was shifted.
This AVP isn’t measuring bits per second it’s measuring kilobits per second.
So the standard Max-Requested-Bandwidth-DL AVP gives us 4.3 Gbps, while the Extended-Max-Requested-Bandwidth gives us a 4,295 Gbps.
We add the Extended-Max-Requested-Bandwidth AVP (4295 Gbps) onto the Max-Requested Bandwidth AVP (4.3 Gbps) giving us a total of 4,4299.3 Gbps.
I started off just updating the SPN, OPN, etc, etc, but I had a suspicion there were still references.
I confirmed this pretty easily with Wireshark, first I started a trace in Wireshark of the APDUs: I enabled capturing on a USB Interface:
modprobe usbmon
Then we need to find where our card reader is connected, running ‘lsusb‘ lists all the USB devices, and you can see here’s mine on Bus 1, Device 49.
Then fired up Wireshark, selected USB Bus 01 to capture all the USB traffic on the bus.
Then I ran the “export” command in PySIM to read the contents of all the files on the SIM, and jumped back over to Wireshark. (PySIM decodes most files but not all – Whereas this method just looks for the bytes containing the string)
From the search menu in Wireshark I searched the packet bytes for the string containing the old brand name, and found two more EFs I’d missed.
For anyone playing along at home, using this method I found references to the old brand name in SMSP (which contains the network name) and ADN (Which had the customer support number as a contact with the old brand name).
Short one, The other day I needed to add a Network Appearance on an SS7/SS7 M3UA linkset.
Network Appearances on M3UA links are kinda like a port number, in that they allow you to distinguish traffic to the same point code, but handled by different logical entities.
When I added the NA parameter on the Linkset nothing happened.
If you’re facing the same you’ll need to set:
cs7 multi-instance
In the global config (this is the part I missed).
Then select the M3UA linkset you want to change and add the network-appearance parameter:
network-appearance 10
And bingo, you’ll start seeing it in your M3UA traffic:
The Binding Support Function is used in 4G and 5G networks to allow applications to authenticate against the network, it’s what we use to authenticate for XCAP and for an Entitlement Server.
Rather irritatingly, there are two BSF addresses in use:
If the ISIM is used for bootstrapping the FQDN to use is:
bsf.ims.mncXXX.mccYYY.pub.3gppnetwork.org
But if the USIM is used for bootstrapping the FQDN is
bsf.mncXXX.mccYYY.pub.3gppnetwork.org
You can override this by setting the 6FDA EF_GBANL (GBA NAF List) on the USIM or equivalent on the ISIM, however not all devices honour this from my testing.
In the past I had my iFCs setup to look for the P-Access-Network-Info header to know if the call was coming from the IMS, but it wasn’t foolproof – Fixed line IMS subs didn’t have this header.
The first thing people learn about SIMs or the Smart Cards that the SIM / USIM app runs on, is that “There’s a little computer in the card”. So how little is this computer, and what’s the computing power in my draw full of SIMs?
So for starters the SIM manufacturers love their NDAs, so I can’t post the chip specifications for the actual cards in my draw, but here’s some comparable specs from a seller selling Java based smart cards online:
Specs for Smart Card
4K of RAM is 4069 bytes. For comparison the Apollo Guidance Computer had 2048 words of RAM, but each “word” was 16 bits (two bytes), so actually this would translate to 4069 bytes so equal with one of these smart cards in terms of RAM – So the smart card above is on par with the AGC that took humans to the moon in terms of RAM, althhough the SIMs would be a wee bit larger if they were also using magnetic core memory like the AGC!
The Nintendo Entertainment System was powered by a MOS Technology 6502, it had access to 2K of RAM, two the Smart Card has twice as much RAM as the NES, so it could get you to the moon and play Super Mario Bros.
What about comparing Non-Volatile Memory (Storage)? Well, the smart card has 145KB of ROM / NVM, while Apollo flew with 36,864 words of RAM, each word is two bits to 73,728 Bytes, so roughly half of what the Smart Card has – Winner – Smart Card, again, without relying on core rope memory like AGC.
SIM cards are clocked kinda funkily so comparing processor speeds is tricky. Smart Cards are clocked off the device they connect to, which feeds them a clock signal via the CLK pin. The minimum clock speed is 1Mhz while the max is 5Mhz.
Now I’m somewhat of a hoarder when it comes to SIM Cards; in the course of my work I have to deal with a lot of SIMs…
Generally when we’re getting SIMs manufactured, during the Batch Approval Process (BAP) the SIM vendor will send ~25 cards for validation and testing. It’s not uncommon to go through several revisions. I probably do 10 of these a year for customers, so that’s 250 cards right there.
Then when the BAP is done I’ll get another 100 or so production cards for the lab, device testing, etc, this probably happens 3 times a year.
So that’s 550 SIMs a year, I do clean out every so often, but let’s call it 1000 cards in the lab in total.
In terms of ROM that gives me a combined 141.25 MB, I could store two Nintendo 64 games, or one Mini CD of data, stored across a thousand SIM cards – And you thought installing software from a few floppies was a pain in the backside, imagine accessing data from 1000 Smart Cards!
What about tying the smart cards together to use as a giant RAM BUS? Well our 1000 cards give us a combined 3.91 MB of RAM, well that’d almost be enough to run Windows 95, and enough to comfortably run Windows 3.1.
Practical do do any of this? Not at all, now if you’ll excuse me I think it’s time I throw out some SIMs…
If you’ve ever worked in roaming, you’ll probably have had the misfortune of dealing with Transferred Account Procedures aka TAP files.
It’s used for billing a 2G GSM call right up to 5G data usage, if you use a service while roaming, somewhere in the world there’s a TAP file with your usage in it.
A brief history of TAP
TAP was originally specified by the GSMA in 1991 as a standard CDR interchange format between operators, for use in roaming scenarios.
Notice I said GSMA – Not 3GPP – This means there’s no 3GPP TS docs for this, it’s defined by the industry lobby group’s members, rather than the standards body.
So what does this actually mean? Well, if you’re MNO A and a customer from MNO B roams into your network, all the calls, SMS and data consumed by the roaming subscriber from MNO B will need to be billed to MNO B, by you, MNO A.
If a network operator wants to get paid for traffic used on their network by roaming subscribers, they’d better send out a TAP file to the roamer’s home network.
TAP is the file format generated my MNO A and sent to MNO B, containing all the usage charges that subscribers from MNO B have racked up while roaming into your network.
These are broken down into “Transactions” (CDRs), for events like making a call, connecting a PDN session and consuming data, or sending a text.
In the beginning of time, GSM provided only voice calling service. This meant that the only services a subscriber could consume while roaming was just making/receiving voice calls which were billed at the end of each month. – This meant billing was equally simple, every so often the visisted network would send the TAP files for the voice calls made by subscribers visited other networks, to the home networks, which would markup those charges, and add them onto the monthly invoice for each subscriber who was roaming.
But of course today, calling accounts for a tiny amount of usage on the network, but this happened gradually while passing through the introduction of SMS, CAMEL services, prepaid services, mobile data, etc. For all these services that could be offered, the TAP format had to evolve to handle each of these scenarios.
As we move towards a flat IP architecture, where voice calls and SMS sent while roaming are just data, TAP files for 4G and 5G networks only need to show data transactions, so the call objects, CAMEL parameters and SMS objects are all falling by the wayside.
What’s inside a TAP File
TAP uses the most beloved of formats – ASN1 to encode the data. This means it is strictly formatted and rigidly specified.
Each file contains a Sequence Number which is a monotonically increasing number, which allows the receiver to know if any files have been missed between the file that’s being currently parsed, an the previous file.
They also have a recipient and sender TADIG code, which is a code allocated by GSMA that uniquely identifies the sender and the recipient of the file.
The TAP records exist in one of two common format, Notification Records and transferBatch records.
These files are exchanged between operators, in practice this means “Dumped on an FTP server as agreed between the two”.
TAP Notification Records
Notifications are the simplest of TAP records and are used when there aren’t any CDRs for roaming events during the time period the TAP file covers.
These are essentially blank TAP files generated by the visited network to let the home network know it’s still there, but there are no roaming subs consuming services in that period.
Notification files are really simple, let’s take a look as one shown as JSON:
When we have services to bill and records to charge, that’s when instead we generate a transferBatch record.
It looks something like this:
There’s a lot going on in here, so let’s break it down section by section.
accountingInfo
The accountingInfo section specifies the currency, exchange rate parameters.
Keep in mind a TAP record generated by an operator in the US, would use USD, while the receiver of the file may be a European MNO dealing in EUR.
This gets even more complicated if you’re dealing with more obscure currencies where an intermediary currency is used, that’s where we bring in SDRs (“Special Drawing Right”) that map to the dollar value to be charged, kinda – the roaming agreement defines how many SDRs are in a dollar, in the example below we’re not using any, but you do see it.
When it comes to numbers and decimal places, TAP doesn’t exactly make it easy.
Significant Digits are defined by counting the first number before the decimal point and all the numbers to the right of the decimal point, so for example the number 1.234 would be 4 significant digits (1 digit before the decimal point and 3 digits after it).
Decimal Places are not actually supported for the Value fields in the TAP file. This is tricky because especially today when roaming tariffs are quite low, these values can be quite small, and we need to represent them as an integer number. TAP defines decimal places as the number of digits after the decimal place.
When it comes to the maximum number of decimal places, this actually impacts the maximum number we can store in the field – as ASN1 strictly enforce what we put in it.
The auditControlInfo section contains the number of CDRs (callEventDetailsCount) contained in the TAP file, the timestamp of the first and last CDR in the file, the total charge and any tax charged.
All of the currency information was provided in the accountingInfo so this is just giving us our totals.
A CDR has 30 days from the time it was generated / service consumed by the roamer, to be baked into a TAP file. After this we can no longer charge for it, so it’s important that the earliestCallTimeStamp is not more than 30 days before the fileCreationTimeStamp seen in batchControlInfo.
batchControlInfo
The batchControlInfo section specifies the time the TAP file became available for transfer, the time the file was created (usually the same), the sequence number and the sender / recipient TADIG codes.
As mentioned earlier, we track sequence number so the receiver can know if a TAP file has been missed; for example if you’ve got TAP file 1 and TAP file 3 comes in, you can determine you’ve missed TAP file 2.
Now we’re getting to the meat & potatoes of our TAP record, the CDRs themselves.
In LTE networks these are just records of data consumption, so let’s take a look inside the gprsCall records under callEventDetails:
In the gprsBasicCallInformation we’ve got as the name suggests the basic info about the data usage event. The time when the session started, the charging ID, the IMSI and the MSISDN of the subscriber to charge, along with their IP and the APN used.
Next up we have the gprsLocationInformation – rates and tariffs may be set based on the location of the subscriber, so we need to identify the area the sub was using the services to select correct tariff / rate for traffic in this destination.
The recEntity is the index number of the SGW / PGW used for the transaction (more on that later).
Next we have the gprsServiceUsed which, again as the name suggests, details the services used and the charge.
chargeDetailList contains the charged data (Made up of dataVolumeIncoming + dataVolumeOutgoing) and the cost.
The chargeableUnits indicates the actual data consumed, however most roaming agreements will standardise on some level of rounding, for example rounding up to the nearest Kilobyte (1024 bytes), so while a sub may consume 1025 bytes of data, they’d be billed for 2045 bytes of data. The data consumed is indicated in the chargeableUnits which indicates how much data was actually consumed, before any rounding policies where applied, while the amount that is actually charged (When taking into account rounding policies) isindicated inside Charged Units.
In the example below data usage is rounded up to the nearest 1024 bytes, 134390 bytes rounds up to the nearest 1024 gives you 135168 bytes.
As this is data we’re talking bytes, but not all bytes are created equal!
VoLTE traffic, using a QCI1 bearer is more valuable than QCI 9 cat videos, and TAP records take this into account in the Call Type Groups, each of which has a different price – Call Type Level 1 indicates the type of traffic, for S8 Home Routed LTE Traffic this is 10 (HGGSN/HP-GW), while Call Type Level 2 indicates the type of traffic as mapped to QCI values:
So Call Type Level 2 set to 20 indicates that this is “20 Unspecified/default LTE QCIs”, and Call Type Level 3 can be set to any value based on a defined inter-operator tariff.
recEntityType 7 means a PGW and contains the IP of the PGW in the Home PLMN, while recEntityType 8 means SGW and is the SGW in the Visited PLMN.
So this means if we reference recEntityCode 2 in a gprsCall, that we’re referring to an SGW at 1.2.3.5.
Lastly also got the utcTimeOffsetInfo to indicate the timezones used and assign a unique code to it.
Using the Records
We as humans? These records aren’t meant for us.
They’re designed to be generated by the Visited PLMN and sent to to the home PLMN, which ingests it and pays the amount specified in the time agreed.
Generally this is an FTP server that the TAP records get dumped into, and an automated bank transfer job based on the totals for the TAP records.
Testing of the TAP records is called “TADIG Testing” and it’s something we’ll go into another day, but in essence it’s validating that the output and contents of the files meet what both operators think is the contract pricing and specifications.
So that’s it! That’s what’s in a TAP record, what it does and how we use it!
GSMA are introducing BCE – Billing & Charging Evolution, a new standard, designed to last for the next 30+ years like TAP has. It’s still in its early days, but that’s the direction the GSMA has indicated it would like to go.
Everything was working on the IMS, then I go to bed, the next morning I fire up the test device and it just won’t authenticate to the IMS – The S-CSCF generated a 401 in response to the REGISTER, but the next REGISTER wouldn’t pass.
When we generate the vectors (for IMS auth and standard auth) one of the inputs to generate the vectors is the Sequence Number or SQN.
This SQN ticks over like an odometer for the number of times the SIM / HSS authentication process has been performed.
There is some leeway in the SQN – It may not always match between the SIM and the HSS and that’s to be expected. When the MME sends an Authentication-Information-Request it can ask for multiple vectors so it’s got some in reserve for the next time the subscriber attaches, and that’s allowed.
But there are limits to how far out our SQN can be, and for good reason – One of the key purposes for the SQN is to protect against replay attacks, where the same vector is replayed to the UE. So the SQN on the HSS can be ahead of the SIM (within reason), but it can’t be behind – Odometers don’t go backwards.
So the issue was with the SQN on the SIM being out of Sync with the SQN in the IMS, how do we know this is the case, and how do we fix this?
Well there is a resync mechanism so the SIM can securely tell the HSS what the current SQN it is using, so the HSS can update it’s SQN.
When verifying the AUTN, the client may detect that the sequence numbers between the client and the server have fallen out of sync. In this case, the client produces a synchronization parameter AUTS, using the shared secret K and the client sequence number SQN. The AUTS parameter is delivered to the network in the authentication response, and the authentication can be tried again based on authentication vectors generated with the synchronized sequence number.
In our example we can tell the sub is out of sync as in our Multimedia Authentication Request we see the SIP-Authorization AVP, which contains the AUTS (client synchronization parameter) which the SIM generated and the UE sent back to the S-CSCF. Our HSS can use the AUTS value to determine the correct SQN.
SIP-Authorization AVP in the Multimedia Authentication Request means the SQN is out of Sync and this AVP contains the RAND and AUTN required to Resync
Note: The SIP-Authorization AVP actually contains both the RAND and the AUTN concatenated together, so in the above example the first 32 bytes are the AUTN value, and the last 32 bytes are the RAND value.
So the HSS gets the AUTS and from it is able to calculate the correct SQN to use.
Then the HSS just generates a new Multimedia Authentication Answer with a new vector using the correct SQN, sends it back to the IMS and presto, the UE can respond to the challenge normally.
Misunderstood, under appreciated and more capable than people give it credit for, is our PCRF.
But what does it do?
Most folks describe the PCRF in hand wavy-terms – “it does policy and charging” is the answer you’ll get, but that doesn’t really tell you anything.
So let’s answer it in a way that hopefully makes some practical sense, starting with the acronym “PCRF” itself, it stands for Policy and Charging Rules Function, which is kind of two functions, one for policy and one for rules, so let’s take a look at both.
Policy
In cellular world, as in law, policy is the rules.
For us some examples of policy could be a “fair use policy” to limit customer usage to acceptable levels, but it can also be promotional packages, services like “free Spotify” packages, “Voice call priority” or “unmetered access to Nick’s Blog and maximum priority” packages, can be offered to customers.
All of these are examples of policy, and to make them work we need to target which subscribers and traffic we want to apply the policy to, and then apply the policy.
Charging Rules
Charging Rules are where the policy actually gets applied and the magic happens.
It’s where we take our policy and turn it into actionable stuff for the cellular world.
Let’s take an example of “unmetered access to Nick’s Blog and maximum priority” as something we want to offer in all our cellular plans, to provide access that doesn’t come out of your regular usage, as well as provide QCI 5 (Highest non dedicated QoS) to this traffic.
To achieve this we need to do 3 things:
Profile the traffic going to this website (so we capture this traffic and not regular other internet traffic)
Charge it differently – So it’s not coming from the subscriber’s regular balance
Up the QoS (QCI) on this traffic to ensure it’s high priority compared to the other traffic on the network
So how do we do that?
Profiling Traffic
So the first step we need to take in providing free access to this website is to filter out traffic to this website, from the traffic not going to this website.
Let’s imagine that this website is hosted on a single machine with the IP 1.2.3.4, and it serves traffic on TCP port 443. This is where IPFilterRules (aka TFTs or “Traffic Flow Templates”) and the Flow-Description AVP come into play. We’ve covered this in the past here, but let’s recap:
IPFilterRules are defined in the Diameter Base Protocol (IETF RFC 6733), where we can learn the basics of encoding them,
They take the format:
action dir proto from src to dst
The action is fairly simple, for all our Dedicated Bearer needs, and the Flow-Description AVP, the action is going to be permit. We’re not blocking here.
The direction (dir) in our case is either in or out, from the perspective of the UE.
Next up is the protocol number (proto), as defined by IANA, but chances are you’ll be using 17 (UDP) or 6 (TCP).
The from value is followed by an IP address with an optional subnet mask in CIDR format, for example from 10.45.0.0/16would match everything in the 10.45.0.0/16 network.
Following from you can also specify the port you want the rule to apply to, or, a range of ports.
Like the from, the tois encoded in the same way, with either a single IP, or a subnet, and optional ports specified.
And that’s it!
So let’s create a rule that matches all traffic to our website hosted on 1.2.3.4 TCP port 443,
permit out 6 from 1.2.3.4 443 to any 1-65535
permit out 6 from any 1-65535 to 1.2.3.4 443
All this info gets put into the Flow-Information AVPs:
With the above, any traffic going to/from 1.23.4 on port 443, will match this rule (unless there’s another rule with a higher precedence value).
Charging Actions
So with our traffic profiled, the next question is what actions are we going to take, well there’s two, we’re going to provide unmetered access to the profiled traffic, and we’re going to use QCI 4 for the traffic (because you’ll need a guaranteed bit rate bearer to access!).
Charging-Group for Profiled Traffic
To allow for Zero Rating for traffic matching this rule, we’ll need to use a different Rating Group.
Let’s imagine our default rating group for data is 10000, then any normal traffic going to the OCS will use rating group 10000, and the OCS will apply the specific rates and policies based on that.
Rating Groups are defined in the OCS, and dictate what rates get applied to what Rating Groups.
For us, our default rating group will be charged at the normal rates, but we can define a rating group value of 4000, and set the OCS to provide unlimited traffic to any Credit-Control-Requests that come in with Rating Group 4000.
This is how operators provide services like “Unlimited Facebook” for example, a Charging Rule matches the traffic to Facebook based on TFTs, and then the Rating Group is set differently to the default rating group, and the OCS just allows all traffic on that rating group, regardless of how much is consumed.
Inside our Charging-Rule-Definition, we populate the Rating-Group AVP to define what Rating Group we’re going to use.
Setting QoS for Profiled Traffic
The QoS Description AVP defines which QoS parameters (QCI / ARP / Guaranteed & Maximum Bandwidth) should be applied to the traffic that matches the rules we just defined.
As mentioned at the start, we’ll use QCI 4 for this traffic, and allocate MBR/GBR values for this traffic.
Putting it Together – The Charging Rule
So with our TFTs defined to match the traffic, our Rating Group to charge the traffic and our QoS to apply to the traffic, we’re ready to put the whole thing together.
So here it is, our “Free NVN” rule:
I’ve attached a PCAP of the flow to this post.
In our next post we’ll talk about how the PGW handles the installation of this rule.
