Spread-Spectrum Techniques for the Provision of Packet ... - CiteSeerX

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 3, APRIL 2004

Spread-Spectrum Techniques for the Provision of Packet Access on the Reverse Link of Next-Generation Broadband Multimedia Satellite Systems Oscar del Rio Herrero, Giuseppe Foti, and Gennaro Gallinaro

Abstract—This paper will examine the potential performances of spread-spectrum-based access techniques via the interaction channel of an Internet protocol (IP)-based multimedia satellite system. In particular, a theoretical analysis of the spread-Aloha technique will be given for the case of forward error correction coded systems. Then, the performance of spread-Aloha access will be confirmed by simulation and compared with that of a conventional time-division multiple-access (TDMA)-based combined free/demand assignment multiple-access system. It appears that spread-Aloha-based techniques, although achieving a lower maximum throughput than the TDMA-based access scheme, may provide a better experience to the user due to the lower transmission latency. Finally, the prospect of a spread-spectrum-based access scheme combining Aloha and reservation mechanisms will be briefly overviewed. Index Terms—Bursty packet traffic, combined free-demand assignment multiple access (CF-DAMA), spread-Aloha, spreadspectrum multiple access.

I. INTRODUCTION

T

RAFFIC in telecommunications networks has evolved from constant regular profiles (e.g., fixed bandwidth voice and video channels) to more dynamic bursty profiles as the number of applications integrated in one network has grown (e.g., voice, data, and video) and also as the usage of network resources by the applications has been optimized (e.g., by using dynamic fixed-quality variable-rate coding techniques). As a result, today’s networks carry traffic that presents burstiness, heavy tails, and self-similarity properties. The successful integration of next-generation Ka-band multimedia satellite systems into the evolving telecommunications networks, calls for the design of new medium access control (MAC) protocols that are optimized for the dynamic traffic characteristics described above. This paper aims at studying the performance of MAC based on spread-spectrum techniques for the reverse link when the Manuscript received December 15, 2002; revised July 1, 2003 and November 10, 2003. O. del Rio Herrero is with the European Space Agency, Noordwijk ZH 2201 AZ, The Netherlands (e-mail: [email protected]). G. Foti was with the European Space Agency, Noordwijk ZH, The Netherlands. He is now with the European Patent Office, Rijswijk 2288 EE, The Netherlands (e-mail: [email protected]). G. Gallinaro is with Space Engineering S.p.A., Rome I-00155, Italy (e-mail: gallinaro@ space.it). Digital Object Identifier 10.1109/JSAC.2004.823440

traffic profiles described above are applied. This paper is organized in two main parts. The first part analyzes spread-Aloha [1] which is mainly based on contention access and allows multipacket reception, and combined free-demand assignment multiple access (CF-DAMA) [2], which is mainly based on demand assignments and shall be used as a benchmark. The second part of this paper introduces a reservation-based asynchronous code-division multiple-access (CDMA) scheme that could be used in combination with spread-Aloha. At a first stage, sensitivity analyses are performed on spreadAloha and CF-DAMA in order to better describe their operation and to see their major advantages and disadvantages. For instance, the sensitivity of spread-Aloha to the processing gain, the required Eb/Nt threshold for successful reception of packets and the power control errors, and the sensitivity of CF-DAMA to the number of active users in the channel are studied. Performance results (throughput, delay, and losses) are shown for each of these two MAC protocols when different traffic profiles (voice, web server, and web client) are applied to the satellite terminals on the return link. Results show that spread-Aloha adapts very well to the packet nature of traffic and to very large populations of users. Finally, a spread-spectrum-based reservation scheme is considered and its performance compared with that provided by spread-Aloha. It will be shown that the reservation-based scheme may slightly improve the performances (throughput and latency) under very heavy loading. Anyway, spread-Aloha appears better performing under not extreme loading conditions. A combination of the two approaches is then evaluated which may provide the advantages of both schemes. II. SYSTEM DESCRIPTION The system scenario in which the performance of the proposed access schemes will be evaluated consists of a population of satellite terminals (STs) transmitting to a gateway station (GW) via a geosynchronous earth orbit (GEO) satellite transparent repeater in the reverse link (RL), while on the forward link (FL) the GW sends reception acknowledgment (ACKs) to the STs. The radio link is modeled as a classical additive white Gaussian noise (AWGN) channel. Propagation delays are those typical of GEO scenarios (250 ms) both in the reverse and forward link.

0733-8716/04$20.00 © 2004 IEEE

DEL RIO HERRERO et al.: SPREAD-SPECTRUM TECHNIQUES FOR THE PROVISION OF PACKET ACCESS

Fig. 1. Spread-Aloha interference model.

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The unslotted case has been analyzed in [3]. However, the analysis has not been specialized for the case in which soft-decision FEC coding (e.g., convolutional or turbo coding) with interleaving over the whole packet is utilized. We expect no significant difference in throughput between the slotted and unslotted variants of spread-Aloha, at least in the idealized case we are considering here, provided that the processing is sufficiently high. This characteristic will be gain1 demonstrated here via simulation. Let us assume an infinite user population with total aggregated traffic offer equal to packet per time slot. The throughput in packet per time slot may be assumed equal to

III. SPREAD-ALOHA A. Interference Model Spread-Aloha has the potential of much better performances than conventional Aloha. As known, conventional Aloha has a limiting efficiency of 18.38% [7]. Moreover, it tends to be strongly unstable in presence of a large user population. In practice, the limiting efficiency of conventional Aloha is difficult to attain in real life. The slotted-Aloha variation doubles the limit efficiency. However, it requires strict time synchronization between users and does not improve the stability problem. The spread-Aloha does not require synchronization like in slotted-Aloha to achieve good efficiency. In fact, by using FEC coding and interleaving, there is no significant difference between the slotted and unslotted access variants. As a matter of fact, with coding and interleaving, we may assume that a packet is lost only if the average interference over the whole packet is higher than a given threshold mainly depending on the coding scheme. The instantaneous interference may well exceed the threshold during the packet reception without this necessarily implying the loss of the packet (this would actually be the case without FEC coding and interleaving). In such a channel the conditions for successful packet reception are the following: • packet detection threshold: average ; • nondestructive collision: no overlap of the same code with being the chip period. Being the signal-to-noise ratio (SNIR) at the receiver side one of the main constraints of this access scheme, an accurate modeling of the interfering power experienced at the reception of each packet needs to be provided. In Fig. 1, we illustrate a typical scenario at the receiver side in which several packets arrive at the demodulator. We need to measure the average value of the interfering power coming from all other packets over the useful packet. Thermal noise shall also be accounted for (AWGN channel). B. Throughput Analysis Below, a throughput analysis of the slotted spread-Aloha case is summarized. In our analysis, we have assumed no thermal noise and no power unbalance. Further, it is assumed that correct packet demodulation happens with probability 1 as long as the average SNIR in the packet exceeds the selected threshold.

where is the probability that a packet is successful. In conventional slotted-Aloha is the probability that no one user select the same slot for transmission. Assuming a Poisson process for packet arrival, it is

Hence

In case slotted spread-Aloha is used, each time slot has length with respect to the unspread case to acgreater of a factor count for the reduction in the data rate (for the same RF channel bandwidth) needed to make room for spreading. However, up to maxCar users can reuse the same time slot before the interference becomes excessive for correct demodulation. is the probability that no In such a case, the probability users select the same time slot for more than other times longer with respect transmission. The slot, however, is to before. Hence, in the Poissonian arrival case, we have

and the throughput expressed in packet per time slot is

Clearly, the throughput expressed in bits per second is obtained by multiplying by the number of bits per packet and dividing the results for the slot period. Hence, the spread-Aloha throughput, normalized to the chip rate is2

1We define the processing gain (P ) as the ratio between the chip rate and the information bit rate (i.e., before FEC coding). This is different from the spreading factor (SF), which is defined as the ratio between the chip rate and the modulation symbol rate before spreading. The P and SF are the same only for uncoded transmission and binary phase-shift keying (BPSK) modulation. 2Such expression should be compared with that of conventional slotted-Aloha T =R = Ge , where R is now representing the modulation symbol rate.

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Fig. 2. Throughput (normalized to chip rate) of slotted spread-Aloha versus the processing gain (PG). The required Eb/Io was assumed equal to 0 dB.

Fig. 4. Normalized throughput of slotted spread-Aloha taking into account the possibility of code collision.

The throughput is then

Fig. 3. Normalized throughput of slotted spread-Aloha under different hypotheses of PG and required Eb/Io.

Fig. 2 shows the achievable throughput for various spreading factor values in the hypothesis that (this is quite simplistic and assumes that an ratio of 0 dB is sufficient for demodulation). increases the normalized It can be seen that as the throughput also increases approaching the limit value of unity. Fig. 3 shows the normalized throughput achievable with slotted spread-Aloha under more realistic assumptions of the . required C. Effect of Code Collisions The previous analysis assumes that there is never collision between spreading codes (i.e., the number of spreading codes is assumed infinite). For a finite number of available codes, there is the possibility the number of available codes. of code collision. Let it be Each user selects a code for transmission in a random way. The probability that a packet is successfully transmitted is now equal to the probability that no more than other maxCar-1 users select the same slot for transmission and that none of the other carrier has selected the same spreading code

Fig. 4 shows the normalized throughput results taking into account the code collision. With the selected parameters, the number of different codes to allocate appears quite high if impact of code collisions on throughput is to be minimized. Anyway, in practice, a lower number of codes with respect to what is indicated in the figure are likely required because the user synchronization is never perfect. Hence, even if two users select the same code for the same time slot, no actual collision could result due to the fact that the two users may have more than one chip period time offset. With unslotted spread-Aloha it can be shown that the required number of different code signatures is much lower [6]. This may bring a significant reduction in the complexity of the GW demodulator bank, notwithstanding some higher criticality in the code acquisition with unslotted access. It shall be underlined that the analysis in preceding sections applies to the case where spreading codes are random. In case of a synchronous CDMA system, orthogonal code may be used in the system. In such cases, when slotted-Aloha is used, we will have an access scheme which we will call orthogonal slotted spread-Aloha. It shall be observed that efficiency in orthogonal slotted spread-Aloha is the same as in conventional slottedAloha. In fact, being codes orthogonal there is no limitation from interference, however, orthogonal codes are limited. D. Simulation Analyses In order to perform a more accurate modeling, in particular for unslotted spread-Aloha which does not lend itself to simple theoretical analysis, a simulation model has been set up in an OPNET Modeler environment. A number of parametric simulations have been run using the unslotted spread-Aloha OPNET model. In all these simulations a backoff time of 2 s (uniform random variable 0–2) and one packet retransmission have been introduced in order to control congestions in the channel. A processing gain of 120 has been assumed, and traffic is generated from 1000 STs following a Poisson arrival process. In order to cope with the long satellite


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Fig. 5. (a) Normalized throughput and ETE delay as a function of the required E =N . (b) Throughput as a function of the power control error.

delays, each ST has the capability to transmit several packets before receiving the ACKs from the GW (i.e., has a transmission window). Packets lost shall be retransmitted on a selective basis. Packets are sent by the ST in a sequential manner in order to avoid self-interference. Fig. 5(a) shows the normalized throughput and average , end-to-end (ETE) delay as a function of the required and Fig. 5(b) as a function of the power control error. For the simulation on the left, we have assumed no power control error, and for the simulation on the right, we have assumed a required of 1.5 dB. As we can see, these two parameters play a decisive role in the performance achieved by unslotted spread-Aloha. We can also notice a good matching with the theoretical of 3 dB, analyses presented in Fig. 3 (e.g., for a required we obtained a normalized throughput of 0.4, which corresponds with the simulated results). From Fig. 5(a), we can see that spread-Aloha is highly sensitive to power control errors. Power control algorithms yielding an error variance not larger than 1 dB shall be necessary.

IV. CF-DAMA For the study of the DAMA techniques, a CF-DAMA scheme using piggy-backed (PB) reservations [2] has been considered. The underlying idea of CF-DAMA is to combine demand assignment with a mechanism that allocates remaining resources in a round-robin fashion to STs on a frame-by-frame basis. Whenever a terminal has been allocated a slot it has also the possibility to demand further capacity using the piggy-backed demand mechanism. The MAC controller holds two tables: a reservation table and a free assignment table. The reservation table is the queue of capacity reservations received by the controller from the STs and it is served in a first-in first-out (FIFO) way. Its entries contain the identification (ID) of the requesting ST and the corresponding amount of requested slots. The free-assignment table is a list of all user stations in the system. This list is initially arranged in a random order. Whenever the reservation queue is empty, the

scheduler assigns the upcoming time slot to the terminal currently on top of free assignment list. This terminal ID is then moved to the bottom of the list. In order to improve fairness and system-level ETE delay, when a ST is assigned a slot on the basis of the reservation table its ID number is also moved to the bottom of the free assignment list. This provides a better chance for STs that do not have any reservations to receive some free-assigned slots and, thus, be able to piggy-back capacity requests on them. A. Simulation Analyses A simulation model has been set up as well in OPNET for CF-DAMA. Our simulation model is based on a contribution from the University of York (U.K.) to the OPNET users’ community [4]. The model has been modified in order to place the DAMA controller on ground in the GW rather than on-board, and the model has been refined in order to improve the simulation speed. In the DAMA simulations, we have assumed a spectral efficiency of 1 bit/Hz/s [e.g., quaternary phase-shift keying (QPSK) ] for the calculation of modulation with coding rate equal to the normalized throughput. Fig. 6 shows the contributions to total throughput originating from the two different assignment mechanisms. At low load there are few explicit requests and most of the throughput comes from free assignments. Then, increasing the load the demand assigned throughput component becomes more and more important till it surpasses the free component. At high load, there are not many free slots left in each frame after the allocation on the basis of the reservation table and the free assigned throughput goes down being replaced by the demand assignment mechanism. In Fig. 7, we can see the sensitivity of CF-DAMA and unslotted spread-Aloha to the number of STs present in the network. As we can see, CF-DAMA is more sensitive to this parameter. The reason is to be found in the free assignment allocation mechanism that becomes inefficient when the number of terminals in the network is very large (i.e., larger than the number of slots in a round-trip delay) as they need to wait for longer delays before they are assigned a free capacity slot. As

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TABLE I SIMULATION TRAFFIC PARAMETERS

Fig. 6.

CF-DAMA throughput decomposition for Poisson type of traffic.

Fig. 8. Spread-Aloha performance for web server type of traffic. Fig. 7.

Sensitivity to the number of terminals.

already said, this free assignment slot is the only way for an ST to start requesting capacity to the system in the CF-DAMA-PB scheme. V. SPREAD-ALOHA VERSUS CF-DAMA-PB PERFORMANCE COMPARISON A. Application Models The traffic models used for the comparison of unslotted spread-Aloha versus CF-DAMA are based on an ETSI model given in [5]. The traffic parameters we have chosen for most of our simulations are summarized in Table I. B. Simulation Results Concerning the spread-Aloha simulation model parameters, only one retransmission is allowed before the packet is discarded. The backoff time is randomly uniformly selected in the range (0, 1.5 s). The processing gain is equal to 100 and the SNIR threshold is set to 1.5 dB. No power control error is taken into account. In order to compare in detail the performance of spread-Aloha versus CF-DAMA-PB, the specific case of a GEO scenario with

web server type of traffic is analyzed. Fig. 8 shows the performance results for the case of spread-Aloha. As it can be seen, a similar performance in terms of throughput is achieved with respect to the Poisson traffic scenario presented in Fig. 5(a) for the case of a SNIR threshold of 1.5 dB. The average delay is 650 ms at all loads and our simulation results have shown that 95% of the packets experience an ETE delay below 700 ms at 50% load. This is due to the fact that only one retransmission is allowed per packet at MAC layer. MAC losses occurrences after one packet retransmission are very low; only 0.06% of the packets are dropped at 50% load. A significant contribution to the delay is represented by the transmission time, in addition to the propagation time. The transmission time is influenced by the packet size. At this regard, a maximum packet size compliant with the traffic model in [5] has been used instead of that reported in Table I. The numbers in Fig. 9 correspond to the number of web server users on each simulation point and the axis represents the normalized generated load. As we can see in Fig. 10, there is almost no contribution to the throughput from the free assignment mechanism (up to 8%). For Poisson type of traffic, we have seen in Fig. 6 that up to 50% of the traffic could come from free assignments yielding an important reduction in terms of ETE delay. Basically, CF-DAMA behaves like pure packet DAMA


Fig. 9.

Fig. 10.

CF-DAMA performance for web server type of traffic.

CF-DAMA throughput decomposition for web server type of traffic.

when bursty traffic sources are used as most of the free assigned slots are wasted. Fig. 11 summarizes the performance in terms of normalized throughput and average ETE delay for all the traffic simulations performed. As we can see, spread-Aloha presents low sensitivity to traffic characteristics and population size. In terms of achievable throughput, CF-DAMA outperforms spread-Aloha at heavier channel loads (60%–80%). VI. SPREAD-ALOHA AND RESERVATION-BASED CDMA ACCESS This section compares the performance of spread-Aloha with that of a reservation-based CDMA access scheme. In a CDMAbased reservation scheme, a ST having outstanding packets in its input queue sends the GW a capacity request in spread-Aloha. Such a request contains an indication of the amount of data waiting in the ST queue, together with parameters (e.g., the measured downlink attenuation) allowing the GW to assign the requesting ST appropriate resources, both in terms of data rate and allocation time. Following allocation, the ST transmits packet(s) containing not only the queued data, but possibly also a “piggyback” request for new capacity. Such last request will only be

Fig. 11.

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Spread-Aloha versus CF-DAMA performance comparison.

issued in case new data gets into the ST queue just while the old queued data are being transmitted. With such technique random requests are minimized, system efficiency is improved and latencies in resource allocation are reduced. A possible optimization, in such a case, is the transmission of short data packets directly in spread-Aloha, i.e., without going through the capacity request protocol. A possible implementation algorithm could perform the following steps every allocation cycle period Tap. • To define an acceptable maximum value ( ) for the , taking into acnoise rise (i.e., the ratio count the ST characteristics (available EIRP and operational bit rates) and the maximum link attenuation taken into account at system design time. • To define the data rate for reservation requests. • To measure at the GW the current noise rise (currNR) and to broadcast the relevant information to STs. • To select at the GW, the access parameters to be broadcast to all STs, based upon currNR, in particular, the GW shall decide the following. — The threshold (in bytes) under which use of randomaccess is allowed for packet transmission. The allowed bit rates are also associated to such a threshold. — The random-access parameters (for both reservation requests and packet transmissions); in particular, the maximum backoff for retransmission after a collision shall be defined. The same access protocol proposed for spread-Aloha is here adopted. • Based upon the access parameters set by the GW, the ST having outstanding data in its MAC queue transmits, by spread-Aloha, a capacity request or directly the data. • The capacity request is stored in a queue at the GW. Every Tap, the GW scheduler is triggered and channel allocations are performed (as discussed later), taking into account system loading, the current noise rise, and the estimated one following the allocation. Also, a check on the required ST EIRP will be done (taking also into account local ST propagation conditions). The GW allocations are in terms of bit rate and period of time a given spreading code remains allocated. The allocation time permits a ST to transmit all data for which the request was made.

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TABLE II RESERVATION-BASED CDMA SIMULATION PARAMETERS

Fig. 13. Performance of reservation CDMA access scheme in an ideal environment. Power-control error variance = 2 dB.

Fig. 12.

Performance of reservation CDMA scheme in an ideal environment.

• A ST receiving an allocation transmits the data. A. Simulation Analyses for Reservation CDMA Scheme A simulation program to the test the performance of the reservation-based CDMA was implemented in C++. The program is able to model a realistic satellite GEO environment, including beam patterns, random user location in the coverage area, thermal noise (through definition of the system temperature of the on-board receiver), packet acquisition preamble. Some of the simulation parameters are summarized in Table II. The ETSI Web server traffic model in [5] was assumed. With respect to parameters shown in Table I, however, the maximum packet size was increased to 64 kB. Moreover, the number of STs was not fixed in the simulation, but a new ST terminal is dynamically generated for each new packet session activated according to an exponential distribution representing the session interarrival time.3 The new session interarrival time is sized according to the required system load. After completion of a session, the ST is removed from the system. Simulation results with an ideal beam pattern are shown in Fig. 12.4 It appears that the maximum throughput is slightly larger with respect to what could be achievable with use of spread-Aloha in the same context. Moreover, the access is fully stable, as witnessed by the fact that no capacity reduction is experienced when the offered load increases; just a delay increase occurs, which is relatively mild when compared with that resulting with spread-Aloha at very high load. 3A hard limit to the maximum number of STs simultaneously active was imposed in the simulator. No new session is generated when this hard limit is reached. This maximum was typically fixed either at 4000 or 8000. 4The ST EIRP was assumed sufficiently high for operating at the required MaxNR.

Sensitivity to power-control errors are instead similar for both reservation-based CDMA and spread-Aloha. The importance of power-control with regard to reverse link efficiency of an asynchronous CDMA system is confirmed by Fig. 13. The reduction in efficiency is similar to that obtained for the spread-Aloha access. Also, the delay knee in case of power-control error is more pronounced with respect to the case of perfect power-control. An accurate power-control is of paramount importance in any asynchronous CDMA-based access scheme, as evident by previous results. To support power-control the following actions are required. • The GW, after any allocation cycle, broadcasts an indicator of the total noise rise which would result in that cycle as a consequence of the granted allocations. Clearly, such noise rise will not take into account the quota of random-access traffic. • Every s the GW also broadcasts every user an indicator of the measured system load averaged over the last s (i.e., the actual measured noise rise, averaged over a 1 s interval). Such indicator, it being the result of an actual measurement and not of just an estimate based on traffic allocations, also takes into account random-access requests, as well as errors in the setting of EIRP, due to power-control errors. • The GW also transmits each user getting a bandwidth allocation, in addition to the allocation message, also the SNIR measured on his request. This parameter can be used by the user to calibrate the open-loop power-control scheme. Moreover the ST has to estimate its uplink attenuation (taking also into account its geographical position and the actual beam gain toward it). Such an estimate may be done by measuring a downlink pilot, and extrapolating the measured attenuation to the uplink, through a suitable frequency-scaling factor. Based , the ST sets up the transmit on estimated uplink attenuation EIRP per bit Nominal

margin

An additional variable called margin has been included in the above EIRP computation. This variable is updated according to GW feedbacks (or lack of feedbacks). In particular, after every successful ST transmission, the GW evaluates the SNIR of the received packet and returns the ST the difference between the measured signal power and the target signal power (referred


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Fig. 14. Reservation CDMA simulation results with perfect power-control in a realistic GEO environment.

Fig. 16. Efficiency and average delay with combined spread-Aloha/ reservation versus access selection threshold. The weighted average delay curve weighs the delay with the packet size. Ideal environment. Session interarrival time = 1 s.

Fig. 15. Results with SNIR measurement error standard dev: = 0:5 dB and power-control loop bias variance equal to 4 dB. No fading.

Fig. 17. Efficiency and average with combined spread-Aloha/reservation versus access selection threshold. The weighted average delay curve weighs the delay with the packet size. Ideal environment. Session interarrival time = 0:5 s.

below as Delta). If the ST receives the feedback, it then updates the margin as: 1) margin margin Delta , where is a constant factor (set equal to 30 in the simulations). If no feedback is received, then the very small aperture terminal (VSAT) updates the margin as was set equal to 1 dB 2) margin margin up, where in the simulations. By this procedure, a suitable margin will be set up for each ST, to compensate for all errors like those occurring in frequency-scaling attenuation, in downlink attenuation measurements, or in estimating the differential beam gain variation between up and down, etc. Furthermore, it will implicitly adapt the ratio obtained at the GW, such as to produce the deare approsired frame error rate (FER), if parameters and priately chosen. Some simulations have been performed using the above illustrated power-control scheme. A GEO system was considered assuming 0.5 dB standard dev. error for the uplink attenuation estimate and a bias of 4 dB (including a possible bias in the power amplifier output setting). Results are shown in Figs. 14 and 15, respectively, for perfect power-control or a control scheme based upon the above procedure. A more realof 4 was assumed in such figures. istic

B. Simulation Analyses for a Combined Spread-Aloha and Reservation CDMA Scheme Combining the two accesses (spread-Aloha and reservation-CDMA) in an adaptive way may be very desirable to get the smaller latency of spread-Aloha under milder channel loading and the better performance under higher loading of reservation-CDMA. A strategy could be that of directly using spread-Aloha for transmitting packets shorter than a given threshold dependent on system loading; in particular the threshold should be higher at lighter loading, in order to exploit the lower spread-Aloha latency under those conditions, whilst spread-Aloha should be fully disabled when the system approaches its maximum capacity. To implement such a strategy, the GW shall compute the threshold basing upon measurements of noise rise and broadcast the computed value to all STs. Figs. 16–18 show the performance of the combined scheme (both in terms of efficiency and average delay) in an ideal environment for different system loading conditions and selected thresholds. The curves labeled Weighted Av. Delay represent the average packet delay, weighted by the packet size.5 In the curve labeled Av. Delay the overall average is instead obtained by computing the average of packet delay 5It is the sum of individual packet delay multiplied the respective packet length (in bytes) and divided by the overall number of bytes transmitted.

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Fig. 18. Efficiency and average with combined spread-Aloha/reservation versus access selection threshold. The weighted average delay curve weighs the delay with the packet size. Ideal environment. Session interarrival time = 0:3 s.

independently of its size and access mode. All the shown results were obtained using a fixed rate for the spread-Aloha mode (32 kb/s), with a transmission window of just one packet (i.e., there can be just one packet waiting for an ACK). The threshold is related to the maximum packet size (in bytes) which can be still transmitted by spread-Aloha through the . From referred figures it relation appears that, for a low-to-medium loaded system, the optimum bytes. Moreover, packet size threshold is about performance (both in terms of efficiency and delay) is not very sensitive with packet size threshold, provided that this is set to at least 400 bytes. For a highly loaded system (Fig. 18), the combined access produces a decrease in throughput, although the delay is still decreased. This result shall, however, be carefully interpreted. In the simulations here reported, in fact, source packets are buffered in an input queue which may contain just one packet. If an additional source packet arrives before the old one has been taken in charge by the MAC for transmission, that packet is discarded. Discarded packets are not included in the packet delay statistics. However, the number of discarded packets is significant for the simulation shown in Fig. 18, as witnessed by the efficiency drop. Hence, it is possible to confirm the statement that reservation CDMA shall be preferred over spread-Aloha for high system loading and vice versa for low loading. C. Combined Spread-Aloha and Reservation CDMA Versus CF-DAMA-PB Performance Comparison In this section, we compare the performance of the combined spread-Aloha and reservation CDMA scheme versus CF-DAMA-PB (see Section IV) for web server type of traffic (see Section V-A). Concerning the combined spread-Aloha and reservation CDMA simulation model parameters, we have assumed an Eb/NT threshold of 1.5 dB, an input queue threshold between spread-Aloha and reservation CDMA mode of 1500 bytes and a maximum input queue of 15 000 bytes. In spread-Aloha mode, a maximum of 1 retransmission, a uniform backoff between 0 and 1.5 s and a maximum MAC frame length of 100 ms have been selected. The simulation model parameters used for CF-DAMA are the same as for Fig. 9. For the web

Fig. 19. Combined spread-Aloha/reservation CDMA versus CF-DAMA performance comparison.

server traffic model, the parameters shown in Table I have been selected except for the packet size, which has a cutoff of 10 000 bytes. As in the reservation CDMA mode, users can achieve data rates up to 256 kb/s (see Table II), a maximum packet size of 10 000 bytes shall be supported with no major impact on the ETE packet delay. Fig. 19 summarizes the results for the combined spread-Aloha and reservation CDMA, and CF-DAMA. As we can see, a combined random/reservation access mechanism performs better than a pure reservation or a hybrid free/demand assignment access mechanism in terms of ETE delay in highly bursty conditions. In terms of normalized throughput, an orthogonal multiple-access scheme such as the one used for CF-DAMA (e.g., TDMA) yields higher link utilization efficiencies than an interference limited multiple-access scheme (e.g., asynchronous CDMA). Combining a quasi-orthogonal spread-spectrum access scheme [8] for reserved traffic with an asynchronous CDMA access scheme for random access traffic could probably achieve a similar link utilization as for TDMA-based access schemes, while keeping the low ETE delay performances specific to the random packet access. VII. CONCLUSION Spread-Aloha performs considerably better than CF-DAMA in terms of ETE delay. In particular, spread-Aloha ETE delay has a low sensitivity to traffic characteristics and population size as long as the access is not overloaded. CF-DAMA can, however, outperform spread-Aloha in terms of achievable throughput at heavier channel loads (60%–80%) due to the orthogonal multiple-access scheme that is used (e.g., TDMA). Using orthogonal multiple-access schemes with capacity reservations will represent a benefit in particular when having applications that generate large amounts of traffic and are not so sensitive to larger ETE delays (e.g., web server). The free assignment mechanism of CF-DAMA is inefficient when used with bursty traffic sources (e.g., web traffic) as compared with the nonbursty scenario with Poisson traffic sources. Its contribution to the traffic throughput is insignificant under bursty traffic conditions. The free assignment mechanism is


actually only used for making capacity reservations by polling the different STs. More efficient mechanisms for making reservations could be envisaged when having scenarios with bursty traffic sources such as contention-based reservation mechanisms. A combination of a reservation CDMA and spread-Aloha, can in fact, bring the advantages of the two mechanisms: reservations and random access. When having low loading in the channel or at user terminal level, spread-Aloha is used yielding very good packet ETE delay performances. When large amounts of data arrive at the user terminal, then reserved transmissions at higher information rates shall help in flushing the input queue rapidly and using the system capacity efficiently. Moreover, it can easily provide guaranteed quality-of-service (QoS) which would be instead more difficult with pure spread-Aloha access. Both spread-spectrum-based access variants can represent a valid alternative to approaches based upon TDMA, especially when the number of served STs is very large. Main advantages are their lower coordination requirements, their better adaptability to different traffic loads, the lower ST RF power requirement and the fact that they better lend themselves to fading and interference mitigation techniques. REFERENCES [1] N. Abramson, “Multiple access in wireless digital networks,” in Proc. IEEE, vol. 82, Sept. 1994, pp. 1360–1370. [2] I. J. Mohammed and T. Le-Ngoc, “Performance analysis of CFDAMA-PB protocol for packet satellite communications,” IEEE Trans. Commun., vol. 46, pp. 1206–1214, Sept. 1998. [3] J. So, I. Han, B. Shin, and D. Cho, “Performance analysis of DS/SSMA unslotted Aloha system with variable length data traffic,” IEEE J. Select. Areas Commun., vol. 19, pp. 2215–2224, Nov. 2001. [4] CFDAMA-PB MAC, P. D. Mitchel. (2001, Jan. 17). [Online]. Available: http://www.opnet.com/support/cont_models.html [5] Selection Procedures for the Choice of Radio Transmission Technologies of the UMTS, ETSI, TR 101.112 v.3.2.0, 1998. [6] Access Design, Space Engineering, Alcatel Bell Space, ASCOM, May 2002. SA3 Deliverable of Advanced S-UMTS Test Bed, ESA Contract N. 15 208. [7] L. Kleinrock, Queueing Systems, Vol 2: Computer Applications. New York: Wiley, 1976. [8] R. De Gaudenzi, C. Elia, and R. Viola, “Bandlimited quasi-synchronous CDMA: A novel satellite access technique for mobile and personal communication systems,” IEEE J. Select. Areas Commun., vol. 10, pp. 328–343, Feb. 1992.

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Oscar del Rio Herrero was born in Barcelona, Spain, in 1971. He received the B.E. degree in telecommunications and the M.E. degree in electronics from the University Ramon Llull, Barcelona, Spain, in 1992 and 1994, respectively, and the Postgraduate degree in space science and technology with emphasis in satellite communications from the Space Studies Institute of Catalonia (IEEC), Barcelona, Spain, in 1995. He joined ESA’s Research and Technology Center (ESTEC), Noordwijk, The Netherlands, in 1996. In 1996 and 1997, he worked as a Radio-Navigation System Engineer in the preparation of the Galileo program. Since 1998, he has worked as a Communications Systems Engineer in the Electrical Systems Department. His current research interests include high-performance on-board processors, packet access and resource management schemes, and IP interworking for future broadband satellite systems.

Giuseppe Foti was born in Catania, Italy, in 1975. He received the Dr. Eng. degree (cum laude) in electronic engineering from the University of Catania, Catania, Italy, in 2000. From 1999 to 2000, he was with Nokia Mobile Phones, Tampere, Finland, where he wrote his thesis on GSM/UMTS interworking in packet data transmission. He was also involved in the standardization activities of the third-generation partnership program (3GPP) and participated in the meetings of the UMTS core network technical working groups (CN1, CN3) as a Nokia delegate. In 2001, he joined the Communication System Section, European Space Agency (ESA), Noordwijk, The Netherlands, where he conducted research in the field of advanced satellite broadband access techniques. He is currently with the European Patent Office (EPO), Rijswijk, The Netherlands, as a Patent Examiner in the Principal Directorate of Telecommunications.

Gennaro Gallinaro received the Dr. Ing. degree in electronic engineering from University of Rome, Rome, Italy, in 1979. From 1981 to 1989, he was with Telespazio, Rome, Italy, where he was involved in satellite communication system planning and design. He is now with Space Engineering, Rome, Italy, where he is involved in several projects, including digital on-board processor design, access design for fixed and mobile satellite systems, simulation software design, and implementation.