To the existing spectrum sharing schemes in wireless-powered cognitive wireless sensor networks,the protocols are limited to either separate the primary and the secondary transmission or allow the secondary user to transmit signals in a time slot when it forwards the primary signal.In order to address this limitation,a novel cooperative spectrum sharing scheme is proposed,where the secondary transmission is multiplexed with both the primary transmission and the relay transmission.Specifically,the process of transmission is on a three-phase time-switching relaying basis.In the first phase,a cognitive sensor node SU1 scavenges energy from the primary transmission.In the second phase,another sensor node SU2 and primary transmitter simultaneously transmit signals to the SU1.In the third phase,the node SU1 can assist the primary transmission to acquire the opportunity of spectrum sharing.Joint decoding and interference cancellation technique is adopted at the receivers to retrieve the desired signals.We further derive the closed-form expressions for the outage probabilities of both the primary and secondary systems.Moreover,we address optimization of energy harvesting duration and power allocation coefficient strategy under performance criteria.An effective algorithm is then presented to solve the optimization problem.Simulation results demonstrate that with the optimized solutions,the sensor nodes with the proposed cooperative spectrum sharing scheme can utilize the spectrum in a more efficient manner without deteriorating the performance of the primary transmission,as compared with the existing one-directional scheme in the literature.
An antenna selection algorithm based on large-scale fading between the transmitter and receiver is proposed for the uplink receive antenna selection in distributed multiple-input multiple-output(D-MIMO) systems. By utilizing the radio access units(RAU) selection based on large-scale fading,the proposed algorithm decreases enormously the computational complexity. Based on the characteristics of distributed systems,an improved particle swarm optimization(PSO) has been proposed for the antenna selection after the RAU selection. In order to apply the improved PSO algorithm better in antenna selection,a general form of channel capacity was transformed into a binary expression by analyzing the formula of channel capacity. The proposed algorithm can make full use of the advantages of D-MIMO systems,and achieve near-optimal performance in terms of channel capacity with low computational complexity.
