An Approximate Analysis of Buffered S-ALOHA in Fading Channels Using Tagged User Analysis

Rasool, S.B.; Sheikh, A.U.H.

doi:10.1109/twc.2007.348328

Cited by 15 publications

(10 citation statements)

References 15 publications

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“…9a, with µ = 0.05 < µ 0 , the network throughput in both cases monotonically increases with q 0 , and is maximized at q 0 = 1. With µ = 1 > µ 0 , on the other hand, the network throughput is maximized at q 0 =q 0 which is given in (28), as Fig. 9b illustrates.…”

Section: Simulation Resultsmentioning

confidence: 99%

Maximum Sum Rate of Slotted Aloha With Successive Interference Cancellation

Dai

2018

IEEE Trans. Commun.

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This is a sequel of our previous work [8] on characterization of maximum sum rate of slotted Aloha networks.By extending the analysis to incorporate the capacity-achieving receiver structure, Successive Interference Cancellation (SIC), this paper aims to identify the rate loss due to random access. Specifically, two representative SIC receivers are considered, i.e, ordered SIC where packets are decoded in a descending order of their received power, and unordered SIC where packets are decoded in a random order. The maximum sum rate and the corresponding optimal parameter setting including the transmission probability and the information encoding rate in both cases are obtained as functions of the mean received signal-to-noise ratio (SNR). The comparison to the capture model shows that the gains are significant only with the ordered SIC at moderate values of the mean received SNR ρ.With a large ρ, the rate gap diminishes, and they all have the same high-SNR slope of e −1 , which is far below that of the ergodic sum capacity of fading channels. The effect of multipacket reception (MPR) on the sum rate performance is also studied by comparing the MPR receivers including SIC and the capture model to the classical collision model. 2 Let us start by summarizing two basic features that are shared by most random-access schemes. 1) Independent Encoding and Uncoordinated Transmissions:Each node independently encodes its information, and decides when to transmit. As the subset of active nodes is random and timevarying, it is normally assumed to be unknown at the transmitter side.2) Time-Slotted and Packet-Based: Though it may not seem to be essential or necessary for random access, a time-slotted and packet-based network has been assumed in the literature since Abramson's Aloha was proposed [5]. Due to the uncoordinated transmissions of nodes, not all the transmitted packets can be successfully decoded in each time slot.With the above features of random access, the number of successfully decoded packets would be varying from time to time. As a result, most studies have focused on the average number of successfully decoded packets per time slot, which is referred to as the network throughput. To analyze the information-theoretic sum rate of a time-slotted packet-based random-access network, a key assumption was further made in [6] that each packet consists of one codeword, and the codeword length is long enough such that a packet can be successfully decoded as long as its information encoding rate does not exceed its single-user capacity, i.e., log 2 (1 + η), where η is the signal-to-interference-plus-noise ratio (SINR) of the packet. Moreover, it is commonly assumed that all the nodes have a uniform information encoding rate if their channel statistics are identical and they are unaware of the instantaneous realization of the channel gains [4], [6], [7]. Under these assumptions, the sum rate of a random-access network is determined by both the encoding rate of each packet and the network throughput.As demonstrated in our rec...

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Section: Simulation Resultsmentioning

confidence: 99%

Maximum Sum Rate of Slotted Aloha With Successive Interference Cancellation

Dai

2018

IEEE Trans. Commun.

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“…Finally, Figure shows that our analysis is a general formulation that encompasses the flat fading analysis of and ideal channel analysis of as special cases. For all cases discussed in the paper, we observe that TUA is able to accurately analyze the system behavior, regardless of the environment over which it is operating.…”

Section: Numerical Results and Discussionmentioning

confidence: 99%

“…TUA has been successfully applied to the analysis of FU‐FB systems for various random access protocols including S‐ALOHA, reservation ALOHA, CSMA with collision detection, and direct sequence Code Division Multiple Access (CDMA) ALOHA for steady channels that are typical of computer networks . TUA has been shown to work in fading channel scenario . In this paper, we have applied TUA to the performance analysis of S‐ALOHA with FU‐GB under multipath frequency selective channel conditions.…”

Section: Introductionmentioning

confidence: 99%

Slotted ALOHA performance for FU-FB in frequency selective fading environment

Masood

Sohail

Sheikh

2013

Wirel. Commun. Mob. Comput.

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Slotted ALOHA is a simple and straightforward random multiple access technique, which has been used extensively in data and cellular networks as the protocol for random access. The complexity of state space-based analysis methods for finite user finite buffer systems increases exponentially with buffer size and number of users. The presence of multipath frequency selective fading channel further adds to the complexity, making the analysis practically intractable. This paper uses an approximate analysis technique called tagged user analysis (TUA) to analyze the performance parameters of slotted ALOHA over multipath and frequency selective fading channels for finite user finite buffer systems. In TUA, the steady state system performance is evaluated from the analysis of a single user. Moreover, the state flow graph of TUA has just four states, thus reducing the complexity of the analysis. Simulation results confirm the validity of the TUA analysis.S-ALOHA performance for FU-FB in freq. sel. fading environment protocols. Access network (infrastructure mode in WiFi) is an important application where multiple users compete for the opportunity to transmit data to an access point [4]. Recent work by [5] investigated the existing S-ALOHA medium access control protocol and suggested some improvements for handling the large propagation delays involved in underwater sensor networks. Theoretical analysis of pure ALOHA and an intuitive explanation of S-ALOHA performance for ultra-wideband were presented in [6]. In [7], researchers studied S-ALOHA-based radio frequency identification system. The analytical results for finding the optimum retransmission probabilities considering S-ALOHA random access protocol with a Poisson arrival process more suitable for the traffic model in a cellular system for the users in the cells were presented in [8]. Cognitive medium access control using S-ALOHA for CR networks was investigated in [9]. S-ALOHA has also been used in other applications including wireless relay networks [10], multi-input multi-output systems [11], wireless mesh networks [12], cooperative transmission [13], framed S-ALOHA-based radio frequency identification systems [14], and wireless sensor networks [15] .The analysis of any wireless communication system entails evaluating a number of system parameters such as, blocking probability, channel throughput, packet drop probability, packet response time, and packet wait delay. The existing MA analysis methods fall in three classes-S-G analysis, Markov analysis, and equilibrium point analysis (EPA) [16]. S-G analysis assumes infinite population, which generates an aggregate traffic of S packets/slot.

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“…Eq. (31) shows that the optimal SINR threshold µ * ,qi=q monotonically decreases as the number of nodes n grows. For large n ≫ 1, it can be obtained from (30-31) that µ * ,qi=q ≈ 1 nq , and…”

Section: A Effect Of Adaptive Backoffmentioning

confidence: 99%

Maximum Sum Rate of Slotted Aloha With Capture

Dai

2016

IEEE Trans. Commun.

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The sum rate performance of random-access networks crucially depends on the access protocol and receiver structure. Despite extensive studies, how to characterize the maximum sum rate of the simplest version of random access, Aloha, remains an open question. In this paper, a comprehensive study of the sum rate performance of slotted Aloha networks is presented. By extending the unified analytical framework proposed in [20], [21] from the classical collision model to the capture model, the network steady-state point in saturated conditions is derived as a function of the signal-to-interference-plusnoise ratio (SINR) threshold which determines a fundamental tradeoff between the information encoding rate and the network throughput. To maximize the sum rate, both the SINR threshold and backoff parameters of nodes should be properly selected. Explicit expressions of the maximum sum rate and the optimal setting are obtained, which show that similar to the sum capacity of the multiple access channel, the maximum sum rate of slotted Aloha also logarithmically increases with the mean received signal-to-noise ratio (SNR), but the high-SNR slope is only e −1 . Effects of backoff and power control on the sum rate performance of slotted Aloha networks are further discussed, which shed important light on the practical network design. .hk).1 Unless otherwise specified, throughout the paper we only consider synchronized slotted networks where the time is divided into multiple slots, and nodes transmit at the beginning of each time slot. was shown to be only e −1 with the collision model [3], which indicates that over 60% of the time is wasted when the network is either in collision or idle states. To improve the efficiency, Carrier Sense Multiple Access (CSMA) was further introduced in [4], with which the network throughput can approach 1 by reducing the sensing time. On the other hand, significant improvement in network throughput was also observed when the capture model is adopted [23]- [32]. Intuitively, with the capture model, more packets can be successfully decoded by reducing the SINR threshold. The network throughput is thus greatly improved, and may exceed 1 if the SINR threshold is sufficiently small.Despite extensive studies, how to maximize the network throughput has been an open question for a long time. In Abramson's landmark paper [3], by modeling the aggregate traffic as a Poisson random variable with parameter G, the network throughput of slotted Aloha with the collision model can be easily obtained as Ge −G , which is maximized at e −1 when G = 1. To enable the network to operate at the optimum point for maximum network throughput, nevertheless, it requires the connection between the mean traffic rate G and key system parameters such as transmission probabilities of nodes, which turns out to be a challenging issue. Various retransmission strategies were developed to adjust the transmission probability of each node according to the number of backlogged nodes to stabilize 2 the network [5]- [8]. Yet most of them ...

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An Approximate Analysis of Buffered S-ALOHA in Fading Channels Using Tagged User Analysis

Cited by 15 publications

References 15 publications

Maximum Sum Rate of Slotted Aloha With Successive Interference Cancellation

Maximum Sum Rate of Slotted Aloha With Successive Interference Cancellation

Slotted ALOHA performance for FU-FB in frequency selective fading environment

Maximum Sum Rate of Slotted Aloha With Capture

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