Joint relay scheduling, channel access, and power allocation for green cognitive radio communications

PublishedJournal Article© 1983-2012 IEEE. The capacity of cognitive radio (CR) systems can be enhanced significantly by deploying relay nodes to exploit the spatial diversity. However, the inevitable imperfect sensing in CR has vital effects on the policy of relay selection, channel access, and power allocation that play pivotal roles in the system capacity. The increase in transmission power can improve the system capacity, but results in high energy consumption, which incurs the increase of carbon emission and network operational cost. Most of the existing schemes for CR systems have not jointly considered the imperfect sensing scenario and the tradeoff between the system capacity and energy consumption. To fill in this gap, this paper proposes an energy-aware centralized relay selection scheme that takes into account the relay selection, channel access, and power allocation jointly in CR with imperfect sensing. Specifically, the CR system is formulated as a partially observable Markov decision process (POMDP) to achieve the goal of balancing the system capacity and energy consumption as well as maximizing the system reward. The optimal policy for relay selection, channel access, and power allocation is then derived by virtue of a dynamic programming approach. A dimension reduction strategy is further applied to reduce its high computation complexity. Extensive simulation experiments and results are presented and analysed to demonstrate the significant performance improvement compared to the existing schemes. The performance results show that the received reward increases more than 50% and the network lifetime increases more than 35%, but the system capacity is reduced less than 6% only.This work was supported by the National Natural Science Foundation of China under Grants 61201219, 61171111, 61472150, and 61173045 and in part by the Fundamental Research Funds for the Central Universities under Grant 2013QN122

Quality of service analysis for hybrid-ARQ

Data intensive applications, requiring reliability and strict delay constraints, have emerged recently and they necessitate a different approach to analyzing system performance. In my work, I establish a framework that relates physical channel parameters to the queueing performance for a single-user wireless system. I then seek to assess the potential benefits of multirate techniques, such as hybrid-ARQ (Automatic Repeat reQuest), in the context of delay-sensitive communications. Present methods of analysis in an information theoretic paradigm define capacity assuming that long codewords can be used to take advantage of the ergodic properties of the fading wireless channel. This definition provides only a limited characterization of the channel in the light of delay constraints. The assumption of independent and identically distributed channel realizations tends to over-estimate the system performance by not considering the inherent time correlation. A finite-state continuous time Markov channel model that I formulate enables me to partition the instantaneous data-rate received at the destination into a finite number of states, representing layers in a hybrid-ARQ scheme. The correlation of channel has been incorporated through level crossing rates as transition rates in the Markov model. The large deviation principle governing the buffer overflow of the Markov model, is very sensitive to channel memory, is tractable, and gives a good estimate of the system performance. Metrics such as effective capacity and probability of buffer overflow, that are obtained through large deviations have been related to the wireless physical layer parameters through the model. Using the above metrics under QoS constraints, I establish the quantitative performance advantage of using hybrid-ARQ over traditional systems. I conduct this inquiry by restricting attention to the case where the expected transmit power is fixed at the transmitter. The results show that hybrid-ARQ helps us in obtaining higher effective capacity, but it is very difficult to support delay sensitive communication over wireless channel in the absence of channel knowledge and dynamic power allocation strategies