Cognitive beamforming exploiting spatial opportunity is an attractive technique for secondary users to coexist with primary users in cognitive radio environments. If perfect channel state information of the interfering link is available, interference from a secondary transmitter to a primary receiver can be perfectly pre-nulled by choosing the ideal transmit beam. In practice, however, there is channel estimation error due to noise and the time-varying channels. To minimize the residual interference due to those channel estimation errors, channel prediction based on auto regressive (AR) model is introduced in this paper. Further, to cope with extremely rapidly-varying channels, a cognitive transmit power control technique is proposed as well. By combining channel prediction and transmit power control in cognitive beamforming, the cognitive users can share the spectrum with the primary users with a limited interference level in time-varying channels.

In this letter, we propose a cdma2000 based MC-CDMA scheme which inherits the same architecture and bandwidth of forward link packet data channel of cdma2000 1x EV-DV. The system utilizes no cyclic prefix, and it uses the bandwidth efficient iterative technique [6] to recover cyclicity of OFDM symbol of the MC-CDMA system to achieve backward compatibility with 1x EV-DV system. We report that the link-level performance of our proposed system is significantly better than previous equalizer-based scheme [7] in frequency selective fading channels.

In this letter, we present an efficient resource allocation algorithm for proportional fair schedulers in mobile multihop relay (MMR) networks. We consider a dual-hop cellular network assisted with a decode-and-forward relay station (RS). Since additional radio resources should be allocated in the wireless link between a base station (BS) and an RS, it is very important to determine the optimal amount of resources for this BS-to-RS link. The proposed resource allocation algorithm maximizes the utility of the overall MMR network in a proportionally fair point of view.