Statistical resource allocation for multi-band Cognitive Radio systems

Abstract

A recent development in wireless communications is Cognitive Radio (CR) technology, an innovative design approach which allows the realization of optimal allocation of the scarce radio resources such as the spectrum. Successful resource allocation in CR systems has to overcome the uncertainty of spectrum bands availability as well as the chaotic wireless propagation environment. Previously, most research in resource allocation in CRs has mainly concentrated on the spectrum opportunity discovery aspect while the robust QoS performance problem has remained largely unexplored. In this paper, we jointly consider the power control and spectrum band discovery problems under uncertain CR operative environments. This problem setting is a direct analogy of the portfolio optimization (PO) concept. In PO, once the variance of return is known, then an investor can use the information to find a wealth allocation strategy so as to minimize the investment risk. Similarly, in uncertain CR scenarios, once the variance of a QoS parameter (e.g., throughput) is known, then a power allocation strategy can be obtained leading to reliable communication. The resulting power strategy also marks out the subbands to be used — essentially achieving soft spectrum sensing. In this work, we shall use the concept of portfolio optimization to jointly achieve power control and subband allocation over uncertain CR environments. The limitations of the approaches are investigated through the sensitivity analysis of the solutions obtained. A raw data processing approach will also be given leading to an alternative algorithm for stable data processing. Numerical results are presented to demonstrate the potential of the proposed approaches.