Multiple Access Protocols for Mobile Communications: GPRS, UMTS and Beyond Alex Brand, Hamid Aghvami Copyright  2002 John Wiley & Sons Ltd ISBNs: 0-471-49877-7 (Hardback); 0-470-84622-4 (Electronic) 8 MD PRMA ON CODE-TIME-SLOTS This chapter is concerned with MD PRMA on perfect-collision code-time-slot channels. The simple and abstract channel model used, representative for a blocking-limited system, allows one to consider an arbitrary number of code-slots E per time-slot, without having to worry about the spreading factor required to meet a certain packet erasure performance. In this framework, the scope of investigations can conveniently be extended to two extreme cases, namely only one code-slot per time-slot, but numerous time-slots N per TDMA frame, and only one time-slot per frame carrying numerous code-slots. In the first case, the CDMA feature is relinquished, and MD PRMA degenerates to pure PRMA. In the second case, the TDMA feature is relinquished. While this configuration (and in fact also PRMA itself) can simply be viewed as a special case of MD PRMA, it actually corresponds to the Reservation-Code Multiple Access (RCMA) protocol proposed in Reference [35]. As in Chapter 7, only voice-traffic will be considered. However, the focus shifts from load-based access control to fixed permission probabilities and backlog-based access control (the latter in the shape of Bayesian broadcast). The performances of pure PRMA, MD PRMA and RCMA will be compared, all with the same number of resource units U = N · E. For MD PRMA with N = 8andE = 8 (i.e. the original UTRA TD/CDMA parameters), the impact of acknowledgement delays and TDD operation on voice dropping performance is also studied. Furthermore, the code-time-slot channel model is enhanced to account for multiple access interference (MAI). In this scenario, unlike the perfect- collision case, load-based access control can make sense. Therefore, on top of ‘conven- tional’ Bayesian broadcast, a scheme combining Bayesian broadcast with a channel access function is considered. 8.1 System Definition and Simulation Approach 8.1.1 System Definition and Choice of Design Parameters The common thread in this chapter is the consideration of code-time-slots based on the TDMA frame duration specified in Section 5.3, namely the 4.615 ms used in GSM and originally proposed for TD/CDMA. However, the focus is not limited to the TD/CDMA scenario with N = 8 time-slots and E = 8 codes per time-slot. Instead, on top of this balanced case, two extreme cases are also considered, namely one with N = 64 time-slots, 312 8 MD PRMA ON CODE-TIME-SLOTS but only one ‘code-slot’ per time-slot, and one with E = 64 codes on a single ‘time- slot’. Effectively, the first case represents pure TDMA, where MD PRMA degenerates to conventional PRMA, and the second case is pure CDMA, for which MD PRMA corresponds to RCMA proposed in Reference [35]. Choosing the same frame duration and the same number of resource units U (namely 64) for all three schemes allows for a fair comparison of their respective performance. For these three cases, MD PRMA for frequency division duplexing as defined in Section 6.2 is investigated, assuming immediate acknowledgement and using either fixed permission probabilities for voice (again the only traffic considered), or backlog-based access control. In the latter case, the voice permission probability p v (or simply p)is calculated according to the Bayesian algorithm adapted for MD PRMA, as outlined in Subsection 6.5.4. Equation (6.9) is used to carry out the estimation of the arrival rate required for this algorithm. Considering an ideal case, the value of p v is broadcast at the end of each time-slot in such a manner that it is available to all mobile stations with full precision before the next time-slot starts. For the scenario with N = 8 time-slots and E = 8 codes per time-slot, the impact of acknowledgement delays is also studied by varying the parameter x introduced in Subsection 6.2.6. This parameter determines how many time-slots a terminal must wait for an acknowledgement following the time-slot in which it sent a packet in contention mode. While waiting, it is not allowed to contend again. In the case of Bayesian broadcast, if x> 0 (i.e. acknowledgement is not immediate), the Bayesian algorithm needs to be modified, that is, p v needs to be calculated through Equation (6.7). Unlike the acknowledgements, p v is assumed to be broadcast immediately at the end of each time-slot. For the same configuration of resource units, the performance of MD FRMA for TDD with a single switching-point per frame, as specified in Subsection 6.3.3, is assessed. From one to eight time-slots per TDMA frame are assumed to be assigned to the uplink direction, where the last case is obviously only of academic interest, since no resources would be available for the downlink in this case. In the following two sections, when more than one code-slot is considered, these slots are assumed to be mutually orthogonal, which means that MAI is ignored. If dedicated channels were used, the system would exhibit hard-blocking, but owing to the PRMA element, it features soft-blocking or soft-capacity. In Section 8.4, on the other hand, MAI is accounted for in the manner specified therein, in order to assess the impact of the loss of orthogonality on access control. In this case, depending on the quality of service requirements, we are dealing with an interference-limited system; that is, excessive packet erasure may prevent all U resource units from being used. In the terminology used in Subsection 7.5.3, ‘U is soft up to an upper limit of N · E’. When interleaving is applied, it is rectangular interleaving over the length of a voice frame, which in turn is carried on four bursts (see Subsection 6.2.4). In this case, request bursts sent in contention mode are dedicated signalling bursts, transmitted on a single code-time-slot. By contrast, when interleaving is not applied, they carry not only signalling, but also user data, namely the same amount as carried by information bursts. For the basic scheme without interleaving, the delay threshold D max is normally set to a small value of 4.615 ms, which is equal to the length of a single TDMA frame. In the case of interleaving, D max is set to the length of a voice frame, i.e. 18.462 ms. To isolate the impact of interleaving and dedicated request bursts, the basic scheme is also operated 8.1 SYSTEM DEFINITION AND SIMULATION APPROACH 313 Table 8.1 Parameters relevant for the physical layer, protocol operation and traffic models Description Symbol Parameter Value TDMA Frame Duration D tf 4.615 ms Time-slots per Frame N 8 (or 64, or 1) Code-slots per Time-slot E 8 (or 1, or 64) Dropping Delay Threshold D max 4.615 ms (no interleaving) 18.462 ms (with interleaving) Mean Talk Gap Duration D gap 1.74 s (or 3 s) Mean Talk Spurt Duration D spurt 1.41 s (or 3 s) with a D max of 18.462 ms in one case. Together with the traffic parameters discussed in the next subsection, all parameters mentioned so far are summarised in Table 8.1. 8.1.2 Simulation Approach, Traffic Parameters and Performance Measures As in the previous chapter, the only traffic considered in the following is packet-voice traffic, using the two-state voice model specified in Section 5.5. Two different parameter sets are considered. The first set, namely D spurt = 1.4sandD gap = 1.74 s, is from the RACE ATDMA project [46], and results in a voice activity factor α v of 0.448, which is slightly higher than that in Chapter 7. As a second set, D spurt = D gap = 3 s taken from Reference [56] is used. This is to establish a link with Chapter 9, where mixed voice and data traffic is considered, and parameters from Reference [56] are used for both voice and Web browsing traffic. The system load is determined by the number of conversations M simultaneously supported, and we are interested in P drop performance as a function of M. Analogous to Chapter 7, M 0.01 and M 0.001 stand for the number of conversations which can be supported at a tolerated P drop , (P drop ) max , of 1% and 0.1% respectively. A static scenario is considered, where P drop is established as a function of M,andM remains fixed over the relevant period of observation. Multiplexing efficiency η mux relative to perfect statistical multiplexing can easily be calculated using Equation (6.1). In Section 8.4, where MAI is accounted for, the relevant figure of merit is P loss instead of P drop , exactly as in Chapter 7. Each simulation-run with fixed M covers 1000 s conversation time. Where required, several simulation-runs were performed for the same value of M,inwhichcaseP drop and P loss reported are the averaged result over these simulation-runs. 8.1.3 Analysis of MD PRMA Pure and modified PRMA systems were analysed for instance in References [135,143,144, 149,150,268,269]. Most of these articles provide a full Markov analysis, some an equi- librium point analysis (EPA). Due to the dimension of the state space with the here considered design parameters, a full Markov analysis is rather challenging. In Refer- ence [61], we provided an EPA for MD PRMA, which expanded on the EPA for PRMA provided in Reference [143] and adopted a few elements of Reference [149]. In certain 314 8 MD PRMA ON CODE-TIME-SLOTS scenarios, we found EPA to be satisfactory, in others not. In the following, we focus on protocol performance assessment through simulation studies. 8.2 Comparison of PRMA, MD PRMA and RCMA Performances 8.2.1 Simulation Results, No Interleaving Figures 8.1 to 8.3 show P drop performance of MD PRMA, PRMA, and RCMA respec- tively, with different fixed p v values (in the figures simply referred to as p) on one hand, and p v calculated through the Bayesian algorithm on the other. In all cases, the basic scheme without interleaving and a very short packet dropping delay threshold D max equal to D tf , namely 4.615 ms, was considered. With MD PRMA (Figure 8.1) and Bayesian Broadcast (BB), M 0.01 = 131 and η mux = 0.92, while M 0.001 = 119 (in which case η mux = 0.83). With fixed p v , M 0.01 lies between 121 (for p v = 0.1) and 131 (p v = 0.3), and M 0.001 peaks at 118 (with p v = 0.5). This seems to indicate that if M 0.01 (or M 0.001 ) were the only performance measure of interest, there would not be much benefit in implementing adaptive access control. However, while it is possible to achieve high capacity with a fixed p v , it is not possible to achieve high capacity with the same p v value which gives low packet dropping at lower load. Further- more, if p v is too large, MD PRMA can become unstable. With the values considered here for M, this was experienced for p v ≥ 0.6andM = 140. In cases in which instability is experienced, P drop results established through simula- tions are heavily affected by the instance in time in which the system first experienced congestion. Once caught in a congested equilibrium point, it is almost certain that the system remains in this state for the remainder of the simulation run and, from then on, 1.0E-8 1.0E-6 1.0E-4 1.0E-2 1.0E+0 60 70 80 90 100 110 120 130 140 150 Simultaneous conversations M Packet dropping ratio P drop p = 0.1 p = 0.2 p = 0.3 p = 0.4 p = 0.5 p = 0.6 p = 0.7 Bayes MD PRMA, N = 8, E = 8 D max = 4.615 ms Figure 8.1 Simulated MD PRMA performance, overview 8.2 COMPARISON OF PRMA, MD PRMA AND RCMA PERFORMANCES 315 the dropping probability is close to one. For values of M for which stability problems were experienced, rather than reporting the average P drop measured over a few simulation runs, which would not deliver statistically relevant results, P drop was simply set to one in Figures 8.1 and 8.2. A better performance measure in such cases would be the so-called First Exit Time (FET) proposed in Reference [194] for slotted ALOHA and applied to PRMA in Reference [149]. The FET is the average first exit time into the unsafe region (i.e. a system state beyond the unstable equilibrium point, see Figure 3.6) starting from an initially empty channel or system. Choosing p v = 0.5 offers the best compromise between capacity (M 0.01 = 128) and low dropping at low load, while appearing to allow for stable operation up to M = 140 (that is, the FET is much larger than the duration of an individual simulation-run). BB on the other hand allows for stable operation at high load while ensuring low packet dropping at low load and performs at least as well as the fixed p v approach over the entire range of M considered. One could argue that the performance of BB could be met by choosing a semi-adaptive approach, i.e. selecting p v depending on M. However, such an approach cannot easily be extended to a mixed traffic scenario, possibly with unknown traffic statistics, whereas BB adapts automatically to different traffic mixes. Furthermore, it would also require regular signalling of p v , leaving reduced computational complexity as the only potential argument in its favour. In view of the very small complexity of BB, this advantage is of no relevance in practice, though. Similar considerations apply in the case of pure PRMA. In fact, looking at Figure 8.2, to avoid stability problems, p v has to be selected even more carefully. Here, with BB, M 0.01 = 129 (η mux = 0.9), and M 0.001 = 119. With fixed p v , M 0.01 lies between 123 (for p v = 0.05) and 129 (p v = 0.2). M 0.001 , on the other hand, although assuming 118 for p v = 0.4, is limited to 114 (p v = 0.2), if the only values of p v considered are those for which the system remains stable up to M = 140. 1.0E-8 1.0E-6 1.0E-4 1.0E-2 1.0E+0 60 70 80 90 100 110 120 130 140 150 Simultaneous conversations M Packet dropping ratio P drop p = 0.05 p = 0.07 p = 0.1 p = 0.15 p = 0.2 p = 0.3 p = 0.4 Bayes PRMA, N = 64, E = 1 D max = 4.615 ms Figure 8.2 Simulated PRMA performance, overview 316 8 MD PRMA ON CODE-TIME-SLOTS 1.0E-6 1.0E-4 1.0E-2 1.0E+0 60 70 80 90 100 110 120 130 140 150 Simultaneous conversations M Packet dropping ratio P drop p = 0.7 p = 0.8 p = 0.9 p = 0.95 p = 0.98 p = 1.0 Bayes RCMA, N = 1, E = 64 D max = 4.615 ms Figure 8.3 Simulated RCMA performance, overview Finally, with RCMA, the situation is slightly different, as illustrated in Figure 8.3. Note first that, since D max = D tf , there is only one contention opportunity for a terminal until the first packet in a spurt is dropped, such that there will be significant dropping irrespec- tive of the load, as soon as p v < 1. In fact, for p v < 0.98 and M ≤ 100, P drop is almost uniquely determined by the waiting probability 1 − p v , which explains the flat segment of the respective curves. On the other hand, even if there is a temporary accumulation of contending terminals, they will normally be able to choose between numerous code-slots available for contention, such that the collision risk is small. Therefore, stability is not an issue even for p v = 1. This in turn means that there is limited benefit in controlling access dynamically, e.g. through Bayesian broadcast, which is also shown in the figure. This is very much in contrast to pure PRMA (and to a lesser extent to MD PRMA), where the accumulation of a few contending terminals C, such that C>1/p v , can result in a number of successive collisions. During these collision slots, C will grow further, and eventually, C  1/p v (orinthecaseofMDPRMA,C  E/p v ), such that the system is bound to become unstable. To complete the discussion of the results for RCMA, with the p v values considered, M 0.01 is between 128 and 129, while with BB, M 0.01 = 130. M 0.001 assumes a value of 118 for both BB and p v = 1. 8.2.2 Performance Comparison and Impact of Interleaving In Reference [35], it is claimed that ‘RCMA is superior to PRMA in terms of system capacity even when a median size of code set is used’. To come to this conclusion, the authors of Reference [35] applied a frequency reuse factor of seven to PRMA, which may be considered conservative, but is probably not completely unrealistic. At the same time however, and curiously enough, the authors spent not a single word on where the ‘median number of codes’ should come from and what kind of bandwidth or spreading factor would be required to support the corresponding number of simultaneous users. For reasons outlined in detail in Sections 3.2 and 5.1, we have no intention of stepping onto a field full of mines by trying to assess the spectral efficiency of TDMA, hybrid 8.3 DETAILED ASSESSMENT OF MD PRMA AND MD FRMA PERFORMANCES 317 1.0E-8 1.0E-6 1.0E-4 1.0E-2 1.0E+0 80 90 100 110 120 130 140 Simultaneous conversations M Packet or frame dropping ratio P drop PRMA MD PRMA RCMA PRMA, interleaving MD PRMA, interleaving RCMA, interleaving Bayesian broadcast D max = 4.615 ms (no interleaving) D max = 18.462 ms (with interleaving) Figure 8.4 PRMA, MD PRMA, and RCMA with Bayesian broadcast CDMA/TDMA, and CDMA systems operating with PRMA, MD PRMA, and RCMA respectively. Here, the focus is exclusively on the efficiency of the multiple access proto- cols as such. From this point of view, the only fair comparison appears to be one based on an equal number of resource units, equal frame duration, and assuming a perfect collision channel for individual units (whether these be code, time, or code-time-slots). This is exactly how Figures 8.1 to 8.3 were obtained, and while the exact P drop behaviour depends on the scheme and the p v value considered, capacity in terms of M 0.01 is virtually identical for these three schemes, namely 130 ± 1. With Bayesian broadcast, even P drop is the same for M>110. The only notable difference is the somewhat higher dropping ratio at low load in the case of RCMA, which is due to the single contention opportunity available before packets are dropped, since D max = D tf . If interleaving over four bursts is applied, and D max is chosen to be D vf (i.e. the length of a voice frame), the excellent agreement between the performance of these three schemes can even be extended to M ≤ 110. This is shown in Figure 8.4. For completeness, as we did already in Section 1.4, we point again at Reference [17], where CDMA, TDMA and hybrid systems are compared from a packet queuing perspective. 8.3 Detailed Assessment of MD PRMA and MD FRMA Performances 8.3.1 Impact of Acknowledgement Delays on MD PRMA Performance It was explained in Section 3.6 why immediate acknowledgements are conceptually impossible with PRMA protocols using frequency division for duplexing. In Subsection 6.2.6 a parameter x was introduced to model acknowledgement delays (see 318 8 MD PRMA ON CODE-TIME-SLOTS also Subsection 8.1.1). With increasing x, one would expect increased P drop ,since unsuccessfully contending terminals spend extra time to get a reservation. On top of that, a value of x greater than zero can also have a negative impact on the accuracy of the backlog estimation through the Bayesian algorithm, even though appropriately enhanced to cope with this situation. This is illustrated in Figures 8.5 and 8.6 for the basic MD PRMA scheme without interleaving, setting D max to 4.615 ms. Figure 8.5 shows the performance achieved with Bayesian broadcast for x = 0to6,and Figure 8.6 compares the performance of Bayesian broadcast with that of perfect backlog estimation (in Chapter 7 referred to as known-backlog-based access control, KBAC) for selected values of x. In both cases, as expected, voice dropping increases with increasing x, particularly at low load. However, while the performance, as far as statistically relevant, is exactly the same for x = 0 (i.e. immediate acknowledgement), the Bayesian algorithm suffers much more with increasing x. The reason is as follows: at low load, the backlog is close to zero in most time-slots, and consequently, p v is set to one. A sudden increase in backlog during a single time- slot period will normally result in a few successive collisions, if the number of available C-slots A[t] is low. This will cause the algorithm to adapt to the situation and lower p v . With x = 0, this can be achieved quickly and packets are rarely dropped. With x>0, collisions will occur with period x + 1 time-slots, so spreading them in time, and the algorithm will need longer to adapt. 1.0E-8 1.0E-6 1.0E-4 1.0E-2 60 70 80 90 100 110 120 130 Simultaneous conversations M Packet dropping ratio P drop x = 6 x = 5 x = 3 x = 2 x = 1 x = 0 MD PRMA, N = 8, E = 8 x : Forbidden time-slots after contention Bayesian broadcast D max = 4.615 ms x = 4 Figure 8.5 Impact of acknowledgement delays on Bayesian broadcast 8.3 DETAILED ASSESSMENT OF MD PRMA AND MD FRMA PERFORMANCES 319 1.0E-8 1.0E-6 1.0E-4 1.0E-2 60 70 80 90 100 110 120 130 Simultaneous conversations M Packet dropping ratio P drop KBAC, x = 6 KBAC, x = 5 KBAC, x = 3 KBAC, x = 0 MD PRMA, N = 8, E = 8 D max = 4.615 ms x : Forbidden time-slots after contention Bayes, x = 6 Bayes, x = 5 Bayes, x = 3 Bayes, x = 0 Figure 8.6 Backlog estimation (Bayes) vs known backlog (KBAC) Even worse, it may be deceived by time-slots with numerous idle and success C-slots lying in-between the ‘collision-time-slots’ (due to other terminals accessing the system in time-slots not affected by collisions). This will further delay the tracking of the real backlog, resulting in packet dropping for those terminals caught in the ‘collision slots’. Interestingly, Bayesian broadcast produces particularly bad results with x = 3, which are even worse than those for x = 4 and 5. Here, a further factor comes into play: not only are collisions repeated every four time-slots, but also the A[t] patterns will exhibit some repetitive behaviour with double this period (i.e. N = 8 time-slots), thus a ‘bad slot’ in terms of backlog may coincide regularly with ‘bad slots’ in terms of low A[t]values. This could probably be described as ‘resonant behaviour’ or ‘local catastrophes’. The comparatively large average P drop in such circumstances is due to a few MS suffering considerable dropping, while those MS never caught in a ‘bad slot’ experience very moderate dropping. Figure 8.7 compares the impact of acknowledgement delays on the performance when using fixed permission probabilities with that when using Bayesian broadcast. The drop- ping performance with p v = 0.2 and 0.3 does not depend on x, since dropping is almost uniquely due to mobile stations not getting permission to send contention packets in this case (because of a large waiting probability 1 − p v ), while C-slot collisions occur rarely. With p v = 0.5, the dropping performance depends to some extent on x, although to a far lesser extent than observed for Bayesian broadcast. With x = 5, any performance advan- tage of the Bayesian approach dwindles away and x = 3 must obviously be avoided for BB, for the reasons just discussed. 320 8 MD PRMA ON CODE-TIME-SLOTS 1.0E-7 1.0E-5 1.0E-3 1.0E-1 60 70 80 90 100 110 120 130 140 150 Simultaneous Conversations M Packet dropping ratio P drop p = 0.2, x = 0 p = 0.3, x = 0 p = 0.5, x = 5 p = 0.5, x = 0 Bayes, x = 5 Bayes, x = 3 Bayes, x = 1 Bayes, x = 0 MD PRMA, N = 8, E = 8 x : Forbidden time-slots after contention D max = 4.615 ms Figure 8.7 Bayesian broadcast vs fixed permission probabilities To mitigate the problem experienced with x = 3, p v calculated with BB could be limited to a maximum value p v max below one, to disrupt the regular coincidence of the two types of ‘bad slots’. However, this would defeat the purpose of broadcast control, which is to stabilise the protocol and ensure efficient operation for all possible traffic scenarios, without having to choose values for traffic dependent parameters, such as p v max . 8.3.2 MD FRMA vs MD PRMA Results shown in Figure 8.8 serve several purposes. They allow the assessment of the impact of: • increasing D max from 4.615 ms to 18.462 ms in the basic MD PRMA scheme (assuming immediate acknowledgement); • the added traffic in the case of interleaving (I/L) due to dedicated request bursts and on average two additional bursts per voice spurt due to rounding up the spurt duration to an integer number of voice frames (again assuming immediate acknowledgement); and • inherent delay of acknowledgements (by an average of slightly less than N/2 time- slots) in the case of MD FRMA (again with interleaving). Note that MD FRMA is considered here with eight uplink time-slots per frame, to compare all schemes with an equal number of uplink time-slots. This effectively means using MD FRMA in FDD mode, which would in practice not leave any time to signal acknowledgements for the entire frame before the subsequent frame starts. [...]... load-based access control with two values for the parameter l 1 The effects of loss of reservations on the performance of this protocol are discussed in Reference [37] 2 This problem did not arise in Chapter 7, since a terminal, while holding a reservation in a certain time-slot, did not reserve a specific code-time-slot it could lose due to transmission failure A corrupted reservation-mode 8.4 COMBINING BACKLOG-BASED... occur immediately, not a single packet or frame was dropped during the simulation period The additional delay incurred by using such packet-based reservation protocols rather than circuit reservations is moderate, it never exceeds Dvf 8.3.3 Performance of MD FRMA in TDD Mode Figure 8.9 depicts the voice dropping performance of MD FRMA in TDD mode with 1, 2, 4, 6, and 8 time-slots in the uplink direction... and Dvf has very limited impact on Pdrop The same can be said about the additional load created by the dedicated request bursts and the impact of interleaving and voice-frame-wise traffic generation and dropping In fact, with Dspurt = 1.41 s, there are on average 305 bursts per talk spurt in the basic scheme, such that the additional traffic load due to one request burst and on average two more information... benchmark, a backlog-based scheme, in certain load conditions Adding to that the above observation on Ppe being dominant, one could wonder whether a combination of backlog-based and load-based access control would not provide a better trade-off between erasure and dropping performance at low load than pure backlog-based access control This has already been discussed in Section 6.6, where we proposed to combine... the following, multiple access interference will be accounted for to study its impact on Bayesian broadcast (cf the respective discussion in Subsection 6.5.8), and to assess the 324 8 MD PRMA ON CODE-TIME-SLOTS benefits of combined backlog-based and load-based access control Regarding the former, recall that increased dropping is expected due to both reduced accuracy of the backlog estimation and packet... basic MD PRMA scheme is considered), and each burst is individually error coded with a (127, 43, 14) BCH code The resulting burst or packet erasure rate Ppe [K] is shown in Figure 5.6 Pro memoria, Ppe [K] is below 10−5 for K ≤ 6, 6.5 × 10−4 for K = 7, 4.1 × 10−3 for K = 8, and 1.6 × 10−2 for K = 9 packets per time-slot The value for K = 9 is indicated because, due to contention, more than eight packets... is quite clear that packet erasure will be an issue at full resource utilisation In fact, depending on the QoS requirements in terms of (Ploss )max , the system will reach its interference limit below a resource utilisation of 100% (note though, that due to the interdependencies between Pdrop and Ppe , it is difficult to establish a precise interference limit for this system) It is assumed that terminals... compensated by this additional traffic Most interestingly, unlike MD PRMA, MD FRMA does not seem to suffer from acknowledgement delays Recall the explanation for the bad performance of MD PRMA with delayed acknowledgements It is clear that allowing terminals to contend repeatedly before receiving feedback in MD FRMA is advantageous, as it allows BB to track the backlog more quickly As an intermediate conclusion,... time-slots By doing so, the impact of trunking efficiency on dropping performance becomes immediately apparent Looking for instance at M0.01 , 12 conversations can be supported with only one timeslot, whereas more than 16 can be supported per time-slot in the case of eight uplink time-slots per frame The findings are very similar to those for the complementary case reported in Reference [49], where E... words, access control is essentially load-based, and the purpose of BB is to contain occasional backlog excursions at high load, avoiding the stability problems experienced with some of the semi-empirical channel access functions (see Section 7.4) 8.5 Summary Assuming immediate acknowledgement and not accounting for interleaving, performances of PRMA, MD PRMA, and RCMA (using TDMA, hybrid CDMA/TDMA, and . are discussed in Reference [37]. 2 This problem did not arise in Chapter 7, since a terminal, while holding a reservation in a certain time-slot, did not. (assuming immediate acknowledgement); • the added traffic in the case of interleaving (I/L) due to dedicated request bursts and on average two additional bursts