The concept of PARPS - Packet And Resource Plan Scheduling

Transcription

1 The concept of PARPS - Packet And Resouce Plan Scheduling Magnus Eiksson 1 and Håkan Sätebeg 2 1) Dept. of Signals, Sensos and Systems, Royal Inst. of Technology, Sweden. magnus.eiksson@ite.mh.se. 2) Dept. of info. tech, Mid Sweden Univesity, Sweden. satha@ite.mh.se Abstact Dynamic schemes fo downlink packet adio esouce management (RRM) ae the topic of this pape. The concept of PARPS (Packet And Resouce Plan Scheduling) is intoduced. PARPS educes the combined poble m of dynamic RRM, including statistical multiplex, dynamic channel allocation, powe contol, link adaptation, euse patitioning, soft handove, admission contol, etc, to a scheduling poblem. PARPS makes it possible to achieve dynamic RRM individually fo each data packet, without pefoming signal-to-intefeence atio calculations fo evey single packet. A PARPS algoithm assigns a so-called esouce plan to each timeslot, and assigns data packets to timeslots and tansmittes. A esouce plan is a combination of seveal adio paametes, e.g. tansmitte powe levels, coding ates and modulation schemes, fo a goup of centally contolled and synchonised tansmittes. We popose seveal optimised and heuistic PARPS algoithms. Optimised PARPS is NP had, i.e. it is not ealistic to solve in eal time fo a big system, but it can be used fo finding an uppe bound fo the compound effect of seveal RRM techniques by means of compute simulations. The heuistic algoithms ae ealistic to implement in eal systems. Ou esults show that some of the heuistic algoithms have delay pefomance vey nea an optimised algoithm, and that the capacity and coveage of a set of esouce plans fo 2D Poisson taffic can be evaluated with static analyses, i.e. without queuing system simulation. We apply PARPS to cellula systems based on the COFDM modulation scheme. Especially, we have pesonal communication sevices in the MEMO system in mind, whee the teestial digital audio o video boadcasting system (DAB o DVB-T) is used as a boadband downlink, in combination with some naowband uplink, e.g. GSM. 1. Intoduction Due to the asymmetic communication mode of client-seve applications, futue cellula systems ae expected to use much moe bandwidth in the downlink than in the uplink. Efficient adio esouce management (RRM) in the downlink is consequently inceasing in impotance. In this pape, we study downlink RRM schemes by assuming that a eliable uplink is aleady established. 1

2 Dynamic RRM techniques such as statistical multiplexing (i.e. packet mode multiple access), dynamic channel allocation, taffic adaptive handove, powe contol, euse patitioning, link adaptation (i.e. dynamic modulation and fowad eo coection), soft handove and admission contol ae often handled by sepaate algoithms on diffeent potocol layes. In this pape we intoduce the concept of Packet And Resouce Plan Scheduling (PARPS), which can be used to combine the above techniques in one algoithm. We assume a system of centally contolled synchonised tansmittes (i.e. access pots), connected with a fast backbone netwok, and using the same fequency channel. We suppose that static cell planning avoids co-channel intefeence between neighbouing systems. We assume that some divesity scheme, e.g. COFDM modulation, avoids fast fading due to multi-path popagation. The complexity of a centalised system is not as sevee poblem in the downlink case as in the uplink, and it is possible to make it vey efficient fom RRM point of view, since we have infomation about all packets in queue. We do not need to intoduce any andom RRM in the system to avoid collisions, such as andom delays o fequency hopping. We combine seveal adio esouce paametes (e.g. the tansmitte powe levels, maco divesity gouping, fowad eo coection codes and modulation schemes) to a numbe of altenative esouce plans. The system ecuently sends test tansmissions of each esouce plan, and each mobile teminal measues what esouce plans it can captue, and epots the measuement esults to the cental system. Altenatively, the teminal measues the gain fom each neighbouing tansmitte, and pehaps also distotion measues such as the time speading and Dopple shift. Based on these measuements the system centally estimates what esouce plans each teminal can captue. The ovehead due to test tansmissions and measuements can be vey small in the fist altenative, if the numbe of esouce plans is estained. A PARPS algoithm dynamically assigns a esouce plan to each timeslot, and assigns the incoming data packets to timeslots and tansmittes. It aims e.g. at minimising the delay, maximising the thoughput, and/o minimising the numbe of dopped packets due to time-to-live violation. In this pape we fomulate seveal optimised and heuistic PARPS algoithms, and evaluate them. Optimised PARPS algoithms give an uppe bound on the pefomance of a given set of esouce plans. We can use optimised PARPS with a lage set of esouce plans to study the combined effect of the dynamic RRM techniques above. Unfotunately, since the optimised PARPS is an assignment optimisation poblem, it is NP had, i.e. its computation time is a nonpolynomial function of the size of the poblem, and it is not ealistic to solve it numeically in eal-time fo big systems. Howeve, it can be used in compute simulations. The heuistic algoithms use polynomial computation time, i.e. they ae scalable and ealistic fo implementation in a eal system. The PARPS concept has the benefit that it can pefom powe contol, link adaptation, etc, fo packets and timeslots individually, but the signal-to-intefeence atio (SIR) does not have to be calculated fo evey single packet and timeslot. In pactical systems, the set of altenative esouce plans must be limited. The set of esouce plans may be changed by means of a slow adaptive pocess. This pocess can be a genetic algoithm, which combines the most popula esouce plans to new esouce plans, and abandons the least popula plans. It may also use conventional algoithms fo static adio netwok planning, powe contol, etc, which uses measuement data to optimise the adio paametes. In this pape, we do not conside adaptive evolution of esouce plans futhe. 2

3 2. System model To be able to evaluate the PARPS concept numeically, we must apply it on a specific system model and poblem aea. We chose to study cellula packet adio systems based on the COFDM modulation scheme. Specifically, we have inteactive sevices in the new teestial digital video and audio boadcasting systems (DVB-T [3] and DAB [2]) in mind. The boadcasting system is supplemented by a naow-band etun channel o inteaction channel [4]. E.g. in the ACT's MEMO (Multimedia Envionment fo Mobiles) poject [5], [6], the DAB system is combined with the GSM system. Examples of applications ae inteactive adio and TV pogammes, and mobile Intenet access with a boadband downlink. A new RRM method which we have poposed [1] is to dynamically goup the tansmittes into Single Fequency Netwoks (SFNs). An SFN is a goup of M=1 tansmittes sending the same infomation simultaneously ove the same channel [7]. The COFDM modulation scheme avoids self-intefeence due to this maco divesity. Ou appoach is to have diffeent SFN fomations in diffeent timeslots. These dynamic SFNs facilitate soft handove, and efficient multicasting (one-to-many) and boadcasting (one-to-all) communication. We assume that the COFDM guad inteval is sufficient fo avoiding inte-symbol intefeence. This gives an aveage signal-to-intefeence atio (SIR) of Γ= N i U 0 GP i i, + GP whee U is the set of M tansmittes in the SFN (the useful signals), I is the set of co-channel intefees, P i the powe fom tansmitte i, G i the popagation gain fom tansmitte i to the teminal, and N 0 the noise powe [7]. Due to shadow fading, 10logG i is No(10log(F/d α i ), σ S ), whee d i is the distance, F is the antenna gain and σ S is the standad deviation in db. Non-ovelapping timeslots ae intoduced in the boadcasting system. We assume that the esouce plan can be changed between two timeslots, and that the timeslots have the same duation in time, independently of the modulation and coding scheme. These assumptions ae simplifications of the poblem, and ae not fully in accodance with today s DAB and DVB-T standads. We neglect the taffic load due to automatic epeat equest (ARQ) etansmissions, and test R4,Z1 tansmissions. R2,Z1 R3,Z1 3. Resouce plans j I The coveage (captue) aea of each SFN o a single tansmitte, such that Γ>γ 0, is hee called a zone. The SIR bound γ 0 includes a magin fo measuement data inaccuacy, e.g. due to teminal motion since last measuement. The magin is based on the measued vaiance of the SIR, and chosen fo a desied pobability of ARQ. Figue 1 shows a simple example with two tansmittes Tx1 and Tx2, and a set of fou esouce plans R1, R2, R3 and R4. In plan R1, both tansmittes send diffeent infomation to two zones (Z1 and Z2), esulting in high co-channel j j R1,Z1 Tx1 R1,Z2 Tx2 (2.1) Fig 1: A simple example. Zone bodes fo fou esouce plans. (The system is noise limited. α=3, ΣP i =1 in evey plan, γ 0 =12dB, σ S =0dB, N 0 /F=0.03.) 3

4 intefeence level and small zones. In R2 and R3 one tansmitte is blocked, esulting in bigge zones. In R4, the tansmittes ae gouped to one SFN, esulting in an inceased total coveage aea. R2, R3 and R4 have one zone each (Z1). The tansmitte plan matix P specifies the tansmitte powe levels and the assignment of tansmittes to zones and esouce plans: powe fom tansmitte i, ifit belongs to zone z of plan, apf,z,i = { 0, othewise, (3.1) whee Œ R = { R1, R2,... }, z Z = { Z1, Z2,... } and i TX { Tx1, Tx2,... } =. The example above is geneated fom the following tansmitte plan matix: P = Z1 Z2 Z1 Z2 Tx1 Tx2 } } } } R1 R2. (3.2) R3 R4 K is the channel euse facto fo plan, hee defined as the numbe of tansmittes pe euse cluste, i.e. TX # of tansmittes in the system K = =. (3.3) Z # of zones in plan In this pape, only symmetical esouce plans ae consideed, implying that all zones in plan has the same SFN size M tansmittes pe SFN. In the example above, M R1 =M R2 =M R3 =1, M R4 =2, TX =2, Z R 1 =2, ZR2 = ZR3 = ZR4 = 1, K R1 =1 and K R2 =K R3 =K R4 =2. If link adaptation is facilitated, we use the SIR bound matix (g),z, which is the SIR theshold of the modulation and coding scheme used in zone z of plan. The data ate matix (R),z specifies the numbe of data packets which can be tansmitted pe timeslot, fo the modulation and coding scheme used in zone z of plan. P and g ae used to calculate if a teminal can captue a cetain zone and esouce plan. R is input to the PARPS algoithm. The capacity η of a esouce plan is the maximum tansmitte utilisation, o the maximum thoughput, i.e. the numbe of data packets that can be sent pe timeslot and tansmitte, and is η = z Z R z, TX. (3.4) If link adaptation is not used, and a timeslot has the same duation length as one packet, η = 1/ K. 4. A static analysis method In this section, we assume a vey simple PARPS algoithm, which uses static handove. We use the tem handove fo the packet to zone and esouce plan assignment. Static handove implies that we do not utilise that the zones ae ovelapping. The handove decisions ae always the same fo a specific teminal position, egadless of the taffic load. R2,Z1 R1,Z1 Tx1 R4,Z1 R3,Z1 R1,Z2 Tx2 Fig 2: Static handove bodes fo the example in figue 1. Plan R1 has pioity ove the othe plans. 4

5 The handove bodes ae statically defined by the set of esouce plans. We also use euse patitioning (RP) without boowing, which implies that the plans may have diffeent capacity η, and that esouce plans with big η (small euse facto K o big data ate R ) ae pioitised in view to maximise the thoughput. A packet is sent ove the zone of the esouce plan which gives sufficient Γ>γ 0 with, fistly, maximum capacity η, and secondly, maximum SIR. Figue 2 shows the cell bodes and the coveage aea fo the combination of R1, R2, R3 and R4 in the example above. Resouce plan R1 has pioity ove the othe plans, because η =1 fo R1, and 0.5 fo R2, R3 and R4, esulting in that R1 has pioity ove R2, R3 and R4. In this static case the bandwidth B assigned to esouce plan (in bps unit o timeslots/time unit) is fixed. Fo maximum capacity, it should be popotional to the expected taffic load λ to plan. If we assume unifom geogaphic taffic distibution, B is popotional to the aea of the cells of plan. E.g. if B R1 =0.5 and B R2 =B R3 =0.25, we use the sequence R1-R2-R1-R3-R1-R2- R1-R3, etc. If we study link adaptation, and all zones of esouce plan ae using the same modulation and coding scheme, B should be popotional to λ /R, whee R is the link bit ate. The capacity of the system is defined as the maximum tansmitte utilisation (the maximum thoughput), i.e. the maximum numbe of tansmitted packets pe timeslot and tansmitte and fequency channel, is fo Poisson taffic B h h max = Â Â B. (4.1) Thus, we can evaluate the capacity and coveage of this static algoithm and a cetain set of esouce plans, fo 2D Poisson taffic, numeically without a queuing system simulation. 5. Scheduling algoithms Figue 3 shows the pevious example with 6 packets in queue, destined to 5 teminal positions. E.g. packet P2 and P6 ae destined to a mobile which can captue zone Z2 in plan R1, Z1 in R2, Z1 in R3, and Z1 in R4. Figue 4 shows a conceivable schedule fo this example. The packet length is equal to the timeslot length in this example. This schedule has minimal aveage delay, because we stat with plan R1 in the fist timeslot, which allows us to tansfe two packets simultaneously. R2,Z1 R4,Z1 R3,Z1 R1,Z1 R1,Z2 Resouce plan: R1 R4 R2 R3 R1 - P1 P4 P2 P5 P6 Zone Z1: Zone Z2: P1 P2 P3 P4 P5 - P6 P3 Fig 3: The example in figue 1, with 6 packets (P1-P6) in queue, destined to 5 teminal positions. Timeslot no : Fig 4: A conceivable schedule. t 5

6 In this section, we popose a numbe of dynamic PARPS algoithms, which utilise that the zones ae ovelapping. 5.1 Optimised scheduling We define the compatibility matix C as: 1, if packet p can be captued in zone z of plan, ( ),, C = zp (5.1) 0, othewise, whee p belongs to the set of packets {P1, P2,...} that have aived to the system and can be captued in at least one esouce plan. In the example in figue 4, the compatibility matix becomes: C = Z1 Z2 Z1 Z2 Z1 Z2 Z1 Z2 Z1 Z2 Z1 Z2 P1 P2 P3 P4 P5 P6 R1 R2 R3 R4. (5.2) The esouce plan to timeslot assignment matix is defined accoding to: 1, if esouce plan is assigned to timeslot t. ( ), R2T = t (5.3) 0, othewise. The packet to timeslot and zone assignment matix is: 1, if packet p is assigned to timeslot t and zone z. ( ),, P2TZ = tzp (5.4) 0, othewise. The schedule in ou example coesponds to: P2TZ= R2T = F HG I KJ R1R2R3R4 q q Z1 Z2 Z1 Z2 Z1 Z2 Z1 Z2 Z1 Z2 Z1 Z2 P1 P2 P3 P4 P5 P6 } t = 0 } t = 1 } t = 2 } t = 3 } t = 4 } t = 5 (5.5) (5.6) 6

7 A PARPS optimisation poblem is solved fo evey timeslot duing which new packets have aived to the system. C is the input to the poblem, and R2T and P2TZ ae the esult. Befoe the poblem is solved, a sufficient numbe N T of timeslots t Œl0, 1,..., N T - 1q in the schedule (numbe of ows in P2TZ and R2T) must be pesumed. In the example above, N T =6. We have fomulated the following fou altenative PARPS optimisation poblems: Opt poblem 1: Minimise the sum of the packet delays: P2TZ (5.7) Minimise D= t ( ) tzp,, p t z subject to ( P2TZ) tzp,, = 1, p (All packets must be scheduled.) z t p t ( P2TZ) ( R2T) ( C), zp,, (The compatibility matix constaint.) tzp,, t, zp,, ( P2TZ) ( R2T) ( R) 0, tz, (Max ( R) packets pe zone and slot.) (5.8) tzp,, t, tzp,, t, z, z, ( R2T) t, = 1, t (One esouce plan pe timeslot.) { } { } ( P2TZ) 0,1, tzp,, ( R2T) 0,1, z,. Optimisation poblem 2: Minimise the maximum packet delay. Minimise Dmax =max t ( ) tzp,, + ( age ) p P2TZ T p, (5.9) t z unde the same constaints as in (4.8). Optimisation poblem 3: Maximise the numbe of scheduled packets. This is an admission contol poblem. We minimise the numbe of skipped packets due to age exceeding the time to live. Thus old packets ae automatically pioitised, as well as packets to teminals nea the tansmittes: Maximise η = ( P2TZ ), (5.10) tot t z p tzp,, unde the same constaints as in (4.8) except the fist, as well as unde the constaints ( P2TZ) tzp,, 1, z t ( ) ( ) p (Packets ae scheduled max once) (5.11) P2TZ t ( ) < T T, p (Time constaints) (5.12) t z tzp,, lifetime age p p whee element p of the vectos T age and T lifetime specifies the numbe of timeslots since the aival of packet p, and its time to live in timeslots, espectively. Optimisation poblem 4: Combination of poblem 3 (fistly) and 2. Minimise admax -h tot, (5.13) whee a is a vey small positive weight. In a non-oveload situation, this acts as poblem 2. These poblems ae optimal scheduling poblems if we lack knowledge to pedict futue packet aivals. In this pape, we only evaluate poblem 1. 7

8 P1 P6 P2 Queue to Z2 Resouce plan R1 P4 P1 P6 P2 Queue to Z2 Resouce plan R1 P4 Resouce plan R2 P6 P4 P2 Resouce plan R2 Incoming packets P5 Resouce plan R3 Incoming packets P6 P5 P4 P2 Resouce plan R3 P3 Resouce plan R4 P6 P5 P4 P3 P2 P1 Resouce plan R4 Fig 5: Local FIFO queue algoithms fo the exampel in figue 3. Fig 6: Centally contolled queue algoithms. A packet can be in seveal queues. 5.2 Heuistic scheduling algoithms We popose ten heuistic scheduling algoithms. They have simila objective functions as the optimisation poblems, but they have a smalle set of feasible solutions. These algoithms can only schedule one packet pe timeslot, i.e. they can not handle link adaptation. Algoithm 1 and 2 ae static schemes based on fixed values of B, and static handove with euse patitioning without boowing, as descibed in section 4. Algoithm 3, 4, 5, 8, 9 and 10 dynamically adopts the esouce plan sequence (the R2T=esouce-plan-to-timeslot assignment) to the taffic. Algoithm 6, 7, 8, 9 and 10 dynamically utilises that the zones ae ovelapping. We categoise the algoithms accoding to the following hieachy: Local FIFO queue algoithms : Thee is a queue to each zone in each esouce plan. The handove decision (the packet to zone and esouce plan assignment decision) is taken immediately when a packet aives. See the example in figue 5. Static handove algoithms put incoming packets in the queue of each cell, accoding to the static handove citeia in section 4. Static R2T: The handove is defined by the static cell bodes and euse patitioning handove ule in section Cyclic R2T. The plan sequence may be R1-R2-R3-R1-R2-R3, etc. B is equal fo all. 2. Weighted R2T. B is popotional to the pobability that a packet uses plan. E.g. if B R1 =0.5 and B R2 =B R3 =0.25, the sequence R1-R2-R1-R3-R1-R2-R1-R3, etc is used. Dynamic R2T: Chooses the esouce plan fo the next timeslot which has 3. most packets in the queues. 4. longest queue. 5. the oldest packet in queue. Taffic adaptive handove: Utilises that the zones ae ovelapping. Incoming packets ae put in the zone with 6. shotest queue. 7. shotest waiting time queue. Centally contolled queue algoithms: All incoming packets ae put in seveal queues, one to each ovelapping zone. See the example in figue 6. When a packet is sent fom one queue, it is emoved fom all the queues. Thus, the handove decision is taken in the moment immediately befoe the tansmission. In the next timeslot, the algoithm uses the esouce plan which 8. can send most packets duing next timeslot. 9. can send the packets with the highest age sum. 10. fistly can send the oldest packet, and secondly, can send most packets. 8

9 6. Simulation esults and conclusions The simulations only conside PARPS algoithms fo a fixed set of symmetic esouce plans with diffeent channel euse (i.e. euse patitioning) and SFN gouping. We do not evaluate powe contol, link adaptation and adaptive evolution of the set of esouce plans at this stage. The duation of a data packet is a timeslot. Fom figue 6 we can daw the conclusion that the centally contolled queue algoithms (cq) have bette mean delay pefomance than the local FIFO queue algoithms (lq) fo 2D Poisson taffic. It is bette to take the handove decision immediately befoe a packet is tansmitted, than to take it when a packet aives to the system. Figue 7 shows that fo busty taffic, centally contolled queue algoithms give a substantial delay and capacity pefomance impovement in compaison to local FIFO queue algoithms. We have numeical esults showing that centally contolled queue algoithms have packet delay pefomance vey nea an optimised PARPS algoithm. E.g. the mean packet delay is 2.13 timeslots of heuistic algoithm 8, and 2.11 of optimisation poblem 1, when η=0.12, K {1,3,4}, {1,2,3,4} 15 Mean packet delay 10 M, γ 0 =12dB, σ S =12dB and N 0 = Mean 50 packet delay Tansmitte utilisation Lq - cyclic tta(1) Lq - weighted tta(2) Lq - Most packets queue(4) Lq - Oldest packet tta(5) Lq - Most packets tta(3) Cq - Most old packets tta(10) Cq- Highest sum of age tta(9) Cq - Most packets tta(8) Tansmitte utilisation Fig 6: 2D Poisson taffic. Compaison of the aveage packet delay in timeslots, as function of the tansmitte utilisation (i.e. the aival intensity) η, in packets pe timeslot and tansmitte, fo nine heuistic algoithms. (K=4. M=1. γ 0 = 12dB. σ S =12dB. N 0 = 0. α=4.) Peliminay numeical esults indicate that fo a 2D Poisson taffic model, all the PARPS algoithms have the same capacity η max (maximum aival ate with stable queue length). Thus, the static analysis method developed in section 4 gives the coveage and capacity of a cetain combination of esouce plans fo any PARPS algoithm, fo 2D Poisson taffic, without queuing system simulation. Howeve, fo busty taffic the dynamic algoithms give a substantial impovement of the capacity in compaison to a static handove algoithm. Futhe eseach activities will be devoted to adaptation of the PARPS concept to the MEMO system and the DAB and DVB-T potocols. evaluation of schemes fo adaptation of the set of esouce plans. the tade-off between the numbe of esouce plans, and the ovehead fo test tansmissions and measuement data. compaison of the pefomance and complexity of the PARPS concept with othe state-ofthe-at RRM schemes. 9

10 Fig 7: Busty taffic. (Poisson taffic to geometically distibuted teminals.) Aveage packet delay vs the aveage numbe of eceives pe tansmittes. (Total aival ate η=0.2 packets pe tansmite and timeslot. Reuse patitioning with K=1, 3, 4 and M=1, 2, 3, 4. γ 0 =12dB. σ S =12dB. N 0 = 0. α=4.) Mean packet delay Lq -Oldest packet tta(5) Cq- Highest sum of age tta (9) Lq shotest queue selectioncyclic tta (6) Aveage numbe of eceives/tansmitte Refeences [1] Eiksson, M., Sätebeg, H., Dynamic adio esouce management schemes fo inteactive sevices in DVB-T and DAB, RVK 99, Kalskona (Sweden), [2] ETSI, Digital Video Boadcasting (DVB); Faming stuctue, channel coding and modulation fo digital teestial television, EN , [3] ETSI, Radio boadcasting systems, Digital Audio Boadcasting (DAB) to mobile, potable and fixed eceives, ETS , [4] E.J Wilson, Intoductoy scenaios fo inteactive television, EBU Technical eview, sping [5] Th. Lautebach, et. al., Using DAB and GSM to Povide Inteactive Multimedia Sevices to Potable and Mobile Teminals, 2nd Euopean Confeence on Multimedia Applications, Sevices and Techniques ECMAST, Milan (Italy) [6] W. Klingenbeg, A. Neutel, MEMO: a hybid DAB/GSM communication system fo mobile inteactive multimedia sevices, Thid Euopean Confeence on Multimedia Applications, Sevices and Techniques ECMAST, Belin, Gemany, [7] Malmgen, G., Single Fequency Boadcasting Netwoks, PhD Thesis, KTH,