Adaptive access and rate control of CSMA for energy, rate, and delay optimization

EURASIP Journal on Wireless Communications and Networking, Jan 2012

In this article, we present a cross-layer adaptive algorithm that dynamically maximizes the average utility function. A per stage utility function is defined for each link of a carrier sense multiple access-based wireless network as a weighted concave function of energy consumption, smoothed rate, and smoothed queue size. Hence, by selecting weights we can control the trade-off among them. Using dynamic programming, the utility function is maximized by dynamically adapting channel access, modulation, and coding according to the queue size and quality of the time-varying channel. We show that the optimal transmission policy has a threshold structure versus the channel state where the optimal decision is to transmit when the wireless channel state is better than a threshold. We also provide a queue management scheme where arrival rate is controlled based on the link state. Numerical results show characteristics of the proposed adaptation scheme and highlight the trade-off among energy consumption, smoothed data rate, and link delay.

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Adaptive access and rate control of CSMA for energy, rate, and delay optimization

Mahdi Khodaian 2 Jess Prez 0 Babak H Khalaj 2 Pedro M Crespo 1 0 Department of Communication Engineering, University of Cantabria , Santander, Spain 1 CEIT and TECNUN (University of Navarra) , 20009, San Sebastian, Spain 2 Department of Electrical Engineering, Sharif University of Technology , Tehran, Iran In this article, we present a cross-layer adaptive algorithm that dynamically maximizes the average utility function. A per stage utility function is defined for each link of a carrier sense multiple access-based wireless network as a weighted concave function of energy consumption, smoothed rate, and smoothed queue size. Hence, by selecting weights we can control the trade-off among them. Using dynamic programming, the utility function is maximized by dynamically adapting channel access, modulation, and coding according to the queue size and quality of the time-varying channel. We show that the optimal transmission policy has a threshold structure versus the channel state where the optimal decision is to transmit when the wireless channel state is better than a threshold. We also provide a queue management scheme where arrival rate is controlled based on the link state. Numerical results show characteristics of the proposed adaptation scheme and highlight the trade-off among energy consumption, smoothed data rate, and link delay. - access schemes are used to efficiently exploit channel resources. In such systems, there are more users than available channels, and at any given time only a subset of users can access the channels. Therefore, the optimality of channel access decision is crucial in random access networks. Random access is widely used in ad hoc networks as it can be implemented in a distributed manner. Wireless local area networks (WLAN) and practical personal or sensor networks usually use random access control in their ad hoc operation mode [9,10]. On the other hand, it is shown recently that CSMA protocols can achieve maximum stable throughput [11] while keeping bounded queuing delay [12], and it can achieve a collision free WLAN [13]. Optimization of random access networks was first proposed in order to achieve single hop proportional fairness for slotted ALOHA networks [14]. Different types of fairness are also considered and random access control is modeled as a utility maximization problem in [15]. In addition, the cross-layer optimization problem of random access control and transmission control protocol is solved as a network utility maximization problem [16]. Newtonlike algorithms are also provided for energy and throughput optimization with end-to-end delay constraint in multi hop random access network [17]. However, in the aforementioned articles static transmission probability was used and opportunity of time varying and adaptive control was ignored. On the other hand, queue-based random access algorithms were studied in [18], where access probabilities are assumed to be adapted based on queue sizes. Stability of the proposed algorithms was verified and their delay performance was shown to surpass fixed optimization algorithms. Also a heuristic differential queue-based scheduling algorithm is proposed in [19] which shows superior performance compared to 802.11 through experimental results. However, such queue-based algorithms are inappropriate for fading channels and prioritize links with low channel quality, which results in low energy efficiency [20]. In this article, we propose cross-layer adaptive algorithms; derived from dynamic programming, for distributed optimization of the links in CSMA-based wireless networks operating in mobile environments. As a performance metric, we define the per stage utility of the link as a weighted concave function of energy consumption, smoothed data rate, and smoothed queue size in the link, where the weights are assigned based on the desired tradeoff among them. The algorithms maximize the average utility by dynamically adapting the channel access decision and transmit data rate (by selecting different modulation and coding schemes) according to the queue size of the link and the availability and quality of the time-varying channel (channel state is assumed to be known at the transmitter). Both, finite-time horizon (FTH) and infinitetime horizon (ITH) problems are considered. In the first case, the utility sum is maximized for a finite time period, whereas in the second case, the long-term average utility is maximized. We consider a mobile environment with frequency-flat time-varying channel response. This requires suitable models of the wireless channel dynamics. Here, we use finite-state Markov chains (FSMC) to model channel dynamics, such that channel time-correlation at network links is partially exploited by the proposed algorithms. Although the physical wireless channel is inherently nonMarkovian, it has been shown that stationary Markov chains can capture the essence of the channel dynamics [21]. Many transmission adaptation algo (...truncated)


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Mahdi Khodaian, Jesús Pérez, Babak H Khalaj. Adaptive access and rate control of CSMA for energy, rate, and delay optimization, EURASIP Journal on Wireless Communications and Networking, 2012, pp. 27, Volume 2012, Issue 1, DOI: 10.1186/1687-1499-2012-27