Joint Soft-Decision Cooperative Spectrum Sensing and Power Control in Multiband Cognitive Radios

We consider joint optimization of cooperative spectrum sensing, channel access and power allocation in an overlay multiband cognitive radio network. A soft-decision cooperative spectrum sensing concept using continuous-valued sensing test statistics is considered, instead of making hard binary decisions as in traditional hypothesis testing spectrum sensing schemes. The channel access decision about whether to access the channel or not is relaxed into allowing the secondary user to access channels with some probability. The sensing decision is made at the secondary base station based on the sensing statistics received from all or a subset of secondary users. This joint optimization problem is aimed at maximizing the secondary users' sum instantaneous throughput while keeping the interference to primary users under a specified threshold. The problem is shown to be a convex optimization problem and the Lagrangian dual method is employed to obtain the optimal solution. Two heuristic algorithms are also proposed to reduce computational complexity. We also discuss an alternative formulation where additionally interference to individual PUs is also constrained. Simulation results show that our soft sensing based algorithm significantly outperforms a traditional hard decision sensing algorithm.