Table Of ContentRandom Access Congestion Control in DVB-RCS2
Interactive Satellite Terminals
Alessio Meloni and Maurizio Murroni
DIEE - Department of Electrical and Electronic Engineering
University of Cagliari
Piazza D’Armi, 09123 Cagliari, Italy
Email: {alessio.meloni}{murroni}@diee.unica.it
Abstract—Thenextgenerationofinteractivesatelliteterminals throughput around 0.36 [packets/slot] despite the possibility
5 isgoingtoplayacrucialroleinthefutureofDVBstandards.As of collision among bursts from different users, SA works
1 a matter of fact in the current standard, satellite terminals are
with very moderate channel load to ensure acceptable delay
0 expectedtobeinteractivethusofferingapartfromthepossibility
and loss probability. This gap has been recently filled with
2 oflogonsignallingandcontrolsignallingalsodatatransmissionin
thereturnchannelwithsatisfyingquality.Consideringthenature the introduction of a new technique named CRDSA that is
n
of the traffic from terminals that is by nature bursty and with able to boost the throughput even up to values close to 1.
a
J big periods of inactivity, the use of a Random Access technique This technique is based on the transmission of a chosen
6 could be preferred. In this paper Random Access congestion number of replicas for each burst payload, similarly to what
control in DVB-RCS2 is considered with particular regard to
2 is done in Diversity Slotted Aloha (DSA) [7]. Burst copies
the recently introduced Contention Resolution Diversity Slotted
Aloha technique, able to boost the performance compared to are randomly placed within a certain number of slots grouped
]
T SlottedAloha.Thepaperanalyzesthestabilityofsuchachannel in a so called frame. However, differently from DSA, in
with particular emphasis on the design and on limit control CRDSA each burst copy has a pointer to the location of the
I
. proceduresthatcanbeappliedinordertoensurestabilityofthe other replicas of the same burst payload. Therefore, when
s
channel even in presence of possible instability due to statistical
c the frame arrives at the receiver an interference cancellation
fluctuations.
[
Index Terms—Transmission, Simulation, Channel Modeling, (IC) process is accomplished. The IC process consists in
1 Congestion Control removing the interfering content of already decoded bursts
v from the remaining slots in which collision occurred, in order
3 I. INTRODUCTION to try restoring the content of bursts that had all their replicas
8
colliding(fromwhichitsname).Inparticular[1]specifiestwo
2 In consumer type of interactive satellite terminals, users
possible variants of CRDSA:
6 generate a large amount of low duty cycle and bursty traffic
0 with frequent periods of inactivity in the return link. Under • ConstantReplicationRatioCRDSA(CR-CRDSA):using
.
1 these operating conditions, the traditionally used Demand As- a constant number of replicas for each burst;
0 signmentMultipleAccess(DAMA)satelliteprotocoldoesnot • Variable Replication Ratio CRDSA (VR-CRDSA): using
5
performoptimally,sincetheresponsetimeforthetransmission anumberofreplicasthatcandifferamongpackets,since
1
: ofshortburstscanbetoolong.Forthisreason,intherecently the number of replicas is determined according to a pre-
v released specification for the next generation of Interactive defined probability distribution.
i
X Satellite Systems (DVB-RCS2) [1], the possibility of sending
Document [1] also claims that the applications using the
logon,controlandevenusertrafficusingRandomAccess(RA)
r
a in timeslots specified by the Network Control Center (NCC) interactive network may rely on network internal contention
control mechanisms to avoid sustained excessive packet loss
is provided to Return Channel Satellite Terminals (RCST). In
resulting from simultaneous destructive transmissions but the
particular,twomethodsareconsideredforRA:thefirstoneis
definition of such a mechanism is claimed to be out of scope
thewellknownSlottedAloha(SA)[2][3],thesecondiscalled
for the document. For this reason, in this paper guidelines
Contention Resolution Diversity Slotted Aloha (CRDSA) [4]
for the design of such a system having simple yet effective
[5] [6].
retransmission policies aiming at avoiding congestion at the
SA represents a well established RA technique for satellite
gateway when using RA in the next generation of satellite
networks in which users send their bursts within slots in
terminals are presented. To do so, we rely on the analysis
a distributed manner, i.e. without any central entity coordi-
carried out in [8], in which a stability model for the case of
nating transmission. While this allows to reach an average
CRDSA with geometrically distributed retransmissions was
A.MelonigratefullyacknowledgesSardiniaRegionalGovernmentforthe presented. The analysis carried out in [8] is based on the
financialsupportofhisPhDscholarship(P.O.R.SardegnaF.S.E.2007-2013 definition of Equilibrium Contour and Channel Load Line,
-AxisIVHumanResources,Objectivel.3,LineofActivityl.3.1.).
similarly to what was done in [9] for SA. The Equilibrium
(cid:13)c2013 IEEE. The IEEE copyright notice applies. DOI:
10.1109/BMSB.2013.6621777 Contour represents a set of circumstances for which the
ongoing communication is in equilibrium, in the sense that
USER 1
the number of newly transmitted packets is equal to the
number of packets successfully sent so that the total number USER 2
of packets ”queuing for retransmission” do not change. The USER 3
Channel Load Line completes the analysis telling which of USER 4
these equilibrium points are actually of equilibrium for a
given scenario, depending on the user population and on the N
s
probability that a user has a new packet to transmit. Based
on this model it is possible to understand where this points of
Figure 1. Example of frame at the receiver for CRDSA with 2 copies per
equilibriumfortheongoingcommunicationarewithrespectto
packet;plainslots indicate thatatransmissionoccurredfor thatuserinthat
thethroughput.Forthisreason,thispaperdiscussesparameter slot.
settings able to ensure that the communication is taking place
in a desirable and stable manner. Moreover, similarly to what
is used in order to inform users about the eventual failure of
was done in [10] for SA, control limit procedures able to
their transmission thus giving birth to a closed loop between
ensure congestion control in DVB-RCS2 when using CRDSA
the transmitter and the receiver. Since this could cause the
as transmission mode are discussed.
channeltogettoastateofcongestion,acertainpolicyableto
II. SYSTEMOVERVIEW retransmit unsuccessful packets and transmit newly generated
packets while keeping the channel in a desirable point of
Consider a multi-access channel populated by a total num-
operation is of great interest.
ber of users M. Users are synchronized so that the channel
is divided into slots and Ns consecutive slots are grouped III. CHANNELSTABILITYMODEL
to constitute a so called frame. The probability that at the
In this section we quickly revise the channel stability
beginning of a frame an idle user has a packet to transmit
model introduced in [8]. Consider the communication system
is p . When a frame starts, users having a packet to transmit
0 introduced in Section II. Each user can be in one of two
place l copies of the same packet over the N slots of that
s states: Thinking (T) or Backlogged (B). Users in T state
frame.Thenumberofcopiesl canbeeitherthesameforeach
are idle users that generate a packet for transmission within
packet or not. Packet copies are nothing else than redundant
a frame interval with probability p ; if they do, no other
0
replicas except for the fact that each one contains a pointer to
packets are generated until successful transmission for that
the location of the others. These pointers are used in order to
packet has been acknowledged. Users in B state are users that
attempt restoring collided packets at the receiver by means of
failed in successfully transmitting their packet and thus are
SuccessiveIC.Forthesakeofsimplicity,throughoutthepaper
attemptingtoretransmitit(theprobabilitythattheyretransmit
perfect IC and channel estimation are assumed which means
is p in each frame). In the followings, we assume that users
r
that the only cause of disturbance for the correct reception
are acknowledged about the success of their transmission at
of packets is interference among them. Moreover, FEC and
the end of the frame (i.e. immediate feedback). From [8], we
possible power unbalance are not considered. Given these
define
conditions, consider the example in Figure 1 representing a
• Nf : backlogged packets at the end of frame f
frame at thereceiver for the caseof 2 copies perpacket. Each B
slot can be in one of three states: • Gf = NB(f−1)pr : expected channel load of frame f due
• no packet’s copies have been placed in a given slot, thus toBusers inNBs state
the slot is idle;
• only1packet’scopyhasbeenplacedinagivenslot,thus • GfT : expected channel load of frame f due to users in
T state
the packet is correctly decoded;
• morethan1packet’scopyhasbeenplacedinagivenslot, • Gf =Gf +Gf : expected total channel load of frame
IN T B
thus resulting in interference of all involved packets. f
InDSA,ifallcopiesforagivenpacketcollidedthepacketis
surelylost.InCRDSA,ifatleastonecopyofacertainpacket • PLRf(GfIN,Ns,l,Imax) : expected packet loss ratio of
frame f, with dependence on the expected total channel
has been correctly received (see User 4), the contribution of
loadG ,theframesizeN ,theburstdegreedistribution
the other copies of the same packet can be removed from the IN s
l and the maximum number of iterations for the SIC
other slots. This process might allow to restore the content
process I
of packets that had all their copies colliding (see User 2) and max
iteratively other packets may be correctly decoded up to a • GfOUT = GfIN(1−PLRf(GfIN,Ns,l,Imax)) : part of
point in which no more packets can be restored (or until the load successfully transmitted in frame f, i.e. throughput.
maximum number of iterations I for the IC process is
max The equilibrium contour can then be described as
reached, if a limit has been fixed).
When a retransmission process is present, if a packet has
not been decoded at the end of the SIC process a feedback G =G =G (1−PLR(G ,N ,l,I )) (1)
T OUT IN IN s max
G PLR(G ,N ,d,I )N
N = IN IN s max s (2)
B
p Channel
r
saturation
For the channel load line, in the case of finite population Channel point Channel
operating operating
while for M → ∞GtThe=chManN−neslNiBnppu0t can be described(a3s) NB Channel load linepoint NB Channel load line point
a Poisson process with expected value λ [thinking users] so G
G T
that T
λ (a) Stablechannel (b) Unstablechannel(finiteM)
G = (4)
T
N
s
for any N (i.e. the expected channel input is constant and
B e
n
independentonthenumberofbackloggedpackets).Noticethat d li Channel
the frame number f is not present, since in equilibrium con- oa saturation
ditions always the same value of throughput and backlogged nel l point
uAs.erDseifisneitxipoencotefdS.tability NB Channel Chan NB Channel load line
operating
Equilibrium contours represented in Figure 2 divide the point
(NB,GT) plane in two parts and each channel load line can GT GT
have one or more intersections with the equilibrium contour.
(c) Unstablechannel(infiniteM) (d) Overloadedchannel
These intersections are referred to as equilibrium points since
G =G . The rest of the points of the channel load line
OUT T Figure2. Examples of stable and unstable channels
belong to one of two sets: those on the left of the equilibrium
contour represent points for which G > G , thus situa-
OUT T
tionsthatyieldtodecreaseofthebackloggedpopulation;those
0.8
on the right represent points for which G < G , thus
OUT T
situations that yield to growth of the backlogged population. 0.7
From the considerations above, we can gather that an
intersection point where the channel load line enters the left 0.6
part for increasing backlogged population corresponds to a
]UT0.5
stable equilibrium point, since it acts as a sink. In particular, O
G
iftheintersectionistheonlyone,thepointisagloballystable put [ 0.4
equilibrium point (indicated as GG,NG) while if more than ugh
T B o
one intersection is present, it is a locally stable equilibrium Thr 0.3
point (indicatedasGS,NS).Ifanintersectionpointentersthe
T B 0.2
right part for increasing backlogged population, it is said to
be an unstable equilibrium point (indicated as GUT,NBU) in the 0.1
sensethatassoonasastatisticalvariationfromtheequilibrium
pointoccurs,thecommunicationwilldivergeinoneofthetwo 0
0 100 200 300 400 500 600 700 800 900 1000
directions of the channel load. f
Figure 2(a) shows a stable channel. The globally stable
equilibrium point can be referred as channel operating point Figure3. SimulationthroughputforCRDSAwithNs=100slots,Imax=
in the sense that we expect the channel to operate around that 20, p0 =0.143, pr =1, M =350 and f indicating the frame sequential
number(i.e.thetimefromthebeginningofthecommunicationinframetime
point. With the word around we mean that due to statistical units.)
fluctuations, the actual G and N (and thus also G and
T B IN
G )maydifferfromtheexpectedvalues.Infact,themodel
OUT
deals with the expected values of G and G , and the actual Figures 2(b) and 2(c) show two unstable channels respec-
T B
valueshavebinomiallydistributedprobabilityforG andG tively for finite and infinite number of users. Analyzing this
B T
with finite M and Poisson distributed probability for G with two figures for increasing number of backlogged packets, the
T
infinite M. Nevertheless, averaging over the entire history of first equilibrium point is a stable equilibrium point. Therefore
the transmission, simulations in [8] have shown that values the communication will tend to keep around it as for the
close to the expected ones are obtained thus validating the stable equilibrium point in Figure 2(a) and we can refer to
assumption of considering the expected value. it once again as channel operating point. However, this is
not the only point of equilibrium since more intersections value; the second is to allow a smaller user population size
are present. Therefore, due to the abovementioned statistical M thus resulting in a waste of capacity. A third solution,
fluctuations, the number of backlogged users could pass the that is the one analyzed in this paper, is the use of control
second intersection and return to the right part of the plane, limit policies to control unstable channels by applying the
causing an unbounded increase of the expected number of countermeasures above in a dynamic manner. In this section
backlogged users in the case of infinite M (Figure 2(c)) or an we analyze control procedures of the limit type able to ensure
increase till a new intersection point is reached in the case of stability. This procedures recall those used in [10] for SA. In
finiteM (Figure2(b)).Inthelattercase,thisthirdintersection particulartwosimpleyeteffectivedynamiccontrolprocedures
point is another stable equilibrium point known as channel are considered: the input control procedure (ICP) and the
saturation point, so called because it is a condition in which retransmission control procedure (RCP). These two control
almost any user is in B state and G approaches zero. In procedures are based upon a subclass of policies known as
OUT
the former case of infinite M, N will increase indefinitely
B
and we can say that a channel saturation point is present for
N → ∞. The effect of this saturation is that the related
B
throughput falls off to a value close to zero as illustrated in
Figure3forthecaseofunstablechannelwithfiniteM.Finally
Figure 2(d) shows the case of an overloaded channel. In this
case there is only one equilibrium point corresponding to the
channelsaturationpoint.Therefore,eventhoughthechannelis NB p0+
nominallystable,thepointofstabilityoccursinanon-desired
region.Forthisreasonthiscaseisseparatedanddistinguished p−
from what is intended in this work as stable channel. 0
IV. DESIGNCHOICESANDPARAMETERSETTINGS
G
T
Given l, N , I , in this section we will extensively dis-
S max
cusstheroleofM,p0,pr andexplainhowthecommunication (a) Changingp0
statechangeswhenchangingthem.Firstofallthisisimportant
in order to understand the relations to be considered in the
design phase. Moreover, the same discussion is introductory
to understand how control policies can help to obtain better
performance and a stable channel even in case of statistical
fluctuations that could yield to instability. B M+
Consider Figure 4. The first thing we can notice is that M N
and p only influence the channel load line while changing
0
p corresponds to a change of the equilibrium contour. In
r
Figure 4(a) we can see that p influences the slope of the M−
0
channel load line that becomes steeper when increasing p .
0 G
This is intuitive to understand since for fixed M, if pA <pB T
0 0
then GA <GB. Figure 4(b) shows that M shifts the channel
T T (b) ChangingM
load line up and down if the population size is respectively
increasing or decreasing. From Equation 3 we can notice that
the value M is nothing else that what is known in literature as
q,thatistheintersectionofthelinewiththey-axis.Finallyp
r
determines a shift upward of the channel load line for smaller p−
r
values of p . As we can see in Figure 4(c) if the value p is
r r
sufficiently small, it is possible to stabilize a channel initially B
N
unstable.Thisrepresentsthegroundbaseforoneofthecontrol
policies shown in the next section.
V. CONTROLLIMITPOLICIES p+
r
Previous sections highlighted that statistical variations can G
T
yield to instability even in case of initially well-performing
channels(seeFigure3).Torenderachannelofthattypestable (c) Changingpr
2 straightforward solutions are available: the first is to use a
smaller value for the retransmission probability giving then Figure 4. Graphical representation of the changes in the (GT,NB) plane
risetoalargerbackloggedpopulationforthesamethroughput whenincreasingordecreasingoneoftheparameters’values.
control limit policies, in which the space of the policies is 2) CRDSAwith3replicas,M =200,p =0.34,p =0.5
0 c
generally composed of two actions and a critical state that resulting in NU =12 when p =1;
B r
determines the switch between them, known as control limit. 3) CRDSAwith2replicas,M =220,p =0.25,p =0.8
0 c
Inthiscasethecontrollimitisacriticalthresholdforacertain resulting in NU =39 when p =1.
B r
number of backlogged users Nˆ .
B
A. Input Control Procedure
This control procedure deals with new packets to transmit. 0.6
In particular, two possible actions are possible: accept (action
a) or deny (action d) and the switch between them is deter-
mined by the threshold Nˆ as previously mentioned. 0.55
B
ut
B. Retransmission Control Procedure p
h 0.5
g
u
As the name says, the retransmission control procedure o
hr
deals with packets to retransmit and in particular with their T
0.45 case 1) with ICP
retransmission probability. In particular two different case 2) with ICP
retransmission probabilities p and p are defined case 3) with ICP
r c case 1) with RCP
that represent respectively the action taken in normal 0.4 case 2) with RCP
retransmission state (action r) and in critical state (action c). case 3) with RCP
From the definition above it is straightforward that it must be
10 20 30 40 50 60 70
pr >pc. The switch between these two modes is determined NˆB
by the threshold Nˆ .
B
Figure6. AveragethroughputversusNˆB
case 1) with ICP
70
case 2) with ICP
case 3) with ICP
60 case 1) with RCP
NB NB pc ˆNB50 ccaassee 23)) wwiitthh RRCCPP
p >
n
NB40
of
G G rate30
T T %
20
(a) ICP (b) RCP
10
Figure5. Controllimitpolicyexamples.
0
10 20 30 40 50 60 70
Figure5showstwoexamplescorrespondingrespectivelyto NˆB
channels using ICP and RCP. As we can see both policies ac-
Figure7. PercentrateofapplicationofthelimitcontrolpolicyversusNˆB
complishthesametaskofensuringchannelstability.However,
while ICP controls the access of thinking users, RCP controls
Figure 6 illustrates the results in terms of throughput both
the access of backlogged users.
forICPandRCPforthestudycasesenumeratedaboveversus
Nˆ .Figure7showstherelatedpercentageofframesinwhich
VI. SIMULATIONRESULTS B
the channel has N > Nˆ so that the critical action of the
B B
Inthissectionweconsidersomecasesofunstablechannels control limit policy is applied (d or c depending on the case).
thatcallforacontrolpolicyabletopreventthemfromsatura- First of all we can notice that both for ICP and for RCP,
tion. In all the cases analyzed M and p0 are fixed (stationary) the range of flatness is wider when operating far from the
and we consider pr = 1 and pc small enough to ensure a throughput peak. This is really important for the following
stable channel. All the scenarios have been simulated for 106 reason.Imaginearealapplicationscenariowithlargedelay(as
frames. The three scenarios considered are the followings: itisthecaseinsatellitecommunications).Differentlyfromthe
1) CRDSAwith3replicas,M =300,p =0.2,p =0.39 caseanalyzedinthispaper,whentheNˆ thresholdiscrossed
0 c B
resulting in NU =25 when p =1; thecontrollimitpolicyneedsacertainpropagationtimebefore
B r
consists in decreasing the retransmission probability (as done
500
in Figure 8 to 0.39). Also in this second case the resulting
Equilibrium contour for case 1) with retx probability p
r
450 Equilibrium contour for case 1) with retx probability p throughput is diminished, although most of the times this
c
400 Channel load line for M=300 and p0=0.2 decrement is of small entity. However another effect is that
Channel load line for M=170 and p0=0.2 theaveragepacketdelayisincreased.Thereforedependingon
350
theapplicationalsothissecondsolutioncouldbeproblematic.
300
VII. CONCLUSIONSANDFUTUREWORK
NB250
Inthispaperamodelforcomputationofthechannelstabil-
200
itywhenusingContentionResolutionDiversitySlottedAloha
150 as Random Access mode in DVB-RCS2 has been outlined.
After analyzing the influence of some crucial parameters such
100
as the transmission and retransmission probability and the
50
population size, the paper introduces the concept of control
0 limit policies for such a technique and outlines empirical
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
G yet effective procedures for congestion control in case of
T
channelsthatpresentthepossibilityofdriftingawaytoazone
Figure8. EquilibriumcontoursforCRDSA3andchannelloadlines of saturation with low throughput. Finally, simulation results
demonstrate how dynamic control limit procedures can help
avoiding congestion while allowing the channel to behave in
it is applied. As a result the effective threshold is not Nˆ but aoptimalmannerdespitethepossibilityofinstabilityandalso
B
some value Nˆ +∆, where ∆ depends on the drift of the in presence of large propagation delay. This work has mainly
B
number of backlogged users for the particular case and on the concentrated on the throughput resulting from the application
propagation delay. Therefore the wider is the flat region, the of this channel procedures. However this represents only half
less the performance optimality of the controlled channel will of the story since also the related packet delay associated
be influenced by the propagation delay. The reason for this to successful packets is of utmost interest. For this reason
difference of flatness can be detected from Figure 7 where it we are currently preparing an extended version of this work
can be noticed that in general terms the number of time spent where also this second aspect is analyzed together with other
in critical state is greater when closer to the throughput peak. important points that have been omitted here for the sake of
This comes from the fact that the operating point of stability concision.
and the point of instability NU are generally closer when
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