Wireless regional area network (WRAN) is intended to offer the fixed wireless access services using cognitive radio technology in the TV white space. Therefore, WRAN shall minimize the transmission power so that harmful interference is not imposed on the licensed users operating in the TV bands. In this paper, we propose a processing block that offers improvements in the SNR and diversity gain using the block to algebraically process two constellation symbols. Thus, the transmission power can be reduced by an amount equal to the gains. The simulation result shows that the proposed scheme has a better bit error performance than the transmission scheme defined in the IEEE 802.22 draft standard.

In this paper, we study the impact of opportunistic user scheduling on the outage probability of cognitive radio (CR) multiple-input multiple-output (MIMO) systems in the high power region where the peak transmit power constraint is higher than the peak interference constraint. The primary contributions of this paper are the derivation of exact closed-form expressions of the proposed scheduled CR-MIMO systems for outage probability and asymptotic analysis to quantify the diversity order and signal to noise ratio (SNR) gain. Through exact analytical results, we provide the achievable outage probability of the proposed scheduled systems as a function of SNR. Also, through asymptotic analysis, we show that the scheduled CR-MIMO systems provide some diversity order gain over the non-scheduled CR-MIMO systems which comes from multi-user diversity (MUD). Also, the SNR gain of the proposed scheduled systems is identical to that of the non-scheduled CR-MIMO systems.

In this paper, low-complexity generalized singular value decomposition (GSVD) based beamforming schemes are proposed for a cognitive radio (CR) network in which multiple secondary users (SUs) with multiple antennas coexist with multiple primary users (PUs). In general, optimal beamforming, which suppresses the interference caused at PUs to below a certain threshold and maximizes the signal-to-interference-plus-noise ratios (SINRs) of multiple SUs simultaneously, requires a complicated iterative optimization process. To overcome the computational complexity, we introduce a signal-to-leakage-plus-noise ratio (SLNR) maximizing beamforming scheme in which the weight can be obtained by using the GSVD algorithm, and does not require any iterations or matrix squaring operations. Here, to satisfy the leakage constraints at PUs, two linear methods, zero forcing (ZF) preprocessing and power allocation, are proposed.

In this paper, performances of two different virtual multiple-input multiple-output (MIMO) transmission schemes — spatial multiplexing (SM) and space-time block coding (STBC) — in a correlated wireless sensor network are analyzed. By utilizing a complex Wishart distribution, we investigate the statistical properties of a correlated virtual MIMO channel between the sensors and data collector that is used in the performance analysis of each MIMO transmission mode. Distributed sensors then transmit their data cooperatively to the data collector by choosing a proper transmission mode adaptively based on the channel conditions and spatial correlation among the sensors. Furthermore, after analyzing the energy efficiencies of SM and STBC, we propose a new energy efficient mode switching rule between SM and STBC. Finally, by analytically deriving the required transmit energy of the proposed adaptive transmission scheme, the manner in which the spatial correlation influences the energy consumption is shown. This suggests a cooperating node scheduling protocol that makes energy consumption less sensitive to the variation of the spatial correlation.