Cross Layer Design for Multiaccess Communication Over Rayleigh Fading Channels

Naware, V.; Tong, Lang

doi:10.1109/twc.2008.06092

Cited by 7 publications

(11 citation statements)

References 14 publications

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“…is used to describe the transmitting error. The outage probability of sensor nodes transmit in a slot is [12]. k…”

Section: The System Modelmentioning

confidence: 99%

An Energy-Efficient Access Control Algorithm with Cross-Layer Optimization in Wireless Sensor Networks

Chen¹,

2010

WSN

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This paper presents a wireless sensor network (WSN) access control algorithm designed to minimize WSN node energy consumption. Based on slotted ALOHA protocol, this algorithm incorporates the power control of physical layer, the transmitting probability of medium access control (MAC) layer, and the automatic repeat request (ARQ) of link layer. In this algorithm, a cross-layer optimization is preformed to minimizing the energy consuming per bit. Through theory deducing, the transmitting probability and transmitting power level is determined, and the relationship between energy consuming per bit and throughput per node is provided. Analytical results show that the cross-layer algorithm results in a significant energy savings relative to layered design subject to the same throughput per node, and the energy saving is extraordinary in the low throughput region

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“…is used to describe the transmitting error. The outage probability of sensor nodes transmit in a slot is [12]. k…”

Section: The System Modelmentioning

confidence: 99%

An Energy-Efficient Access Control Algorithm with Cross-Layer Optimization in Wireless Sensor Networks

Chen¹,

2010

WSN

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“…It was first pointed out by Roberts in [22] that even with multiple concurrent transmissions, the strongest signal could be successfully detected as long as the signal-to-interference ratio (SIR) is high enough. It was referred to as the "capture effect", which has been extensively studied in [23]- [36]. With the capture model, each node's packet is decoded independently by treating others' as background noise.…”

Section: Introductionmentioning

confidence: 99%

“…In[34], for instance, "average spectral efficiency" was used to denote the sum rate of slotted Aloha. In[19],[35],[36],[42], it was referred to as "throughput".…”

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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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“…Research on cross-layer design (CLD) optimization has generated a lot of interest in recent years [1][2][3][4]. It shares information between protocol layers [5].…”

Section: Introductionmentioning

confidence: 99%