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The paper investigates the problem of maximizing expected sum throughput in afading multiple access cognitive radio network when secondary user (SU)transmitters have energy harvesting capability, and perform cooperativespectrum sensing. We formulate the problem as maximization of sum-capacity ofthe cognitive multiple access network over a finite time horizon subject to atime averaged interference constraint at the primary user (PU) and almost sureenergy causality constraints at the SUs. The problem is a mixed integernon-linear program with respect to two decision variables namely spectrumaccess decision and spectrum sensing decision, and the continuous variablessensing time and transmission power. In general, this problem is known to be NPhard. For optimization over these two decision variables, we use an exhaustivesearch policy when the length of the time horizon is small, and a heuristicpolicy for longer horizons. For given values of the decision variables, theproblem simplifies into a joint optimization on SU \textit{transmission power}and \textit{sensing time}, which is non-convex in nature. We solve theresulting optimization problem as an alternating convex optimization problemfor both non-causal and causal channel state information and harvested energyinformation patterns at the SU base station (SBS) or fusion center (FC). Wepresent an analytic solution for the non-causal scenario with infinite batterycapacity for a general finite horizon problem.We formulate the problem withcausal information and finite battery capacity as a stochastic control problemand solve it using the technique of dynamic programming. Numerical results arepresented to illustrate the performance of the various algorithms.

Sensing Throughput Optimization in Fading Cognitive Multiple Access Channels With Energy Harvesting Secondary Transmitters