We propose a two-phase diversity scheme to achieve the end-to-end spatial diversity gain for physical-layer network coding (PNC) based two-way relay with a multiple-antenna relay node. A novel binary PNC-specific maximal-ratio-combining like (MRC-L) scheme is proposed to obtain receive diversity in the multiple-access (MA) phase with linear complexity; the Max-Min criterion based transmit antenna selection (TAS) is adopted to obtain transmit diversity in the broadcast (BC) phase. Both the brief diversity analysis and the Monte Carlo (MC) simulation results demonstrate that the proposed scheme achieves full diversity and outperforms other comparable schemes in terms of end-to-end diversity or power advantage.

Focusing on time correlation of real communication channels, a channel quantization algorithm based on finite state vector quantization (FSVQ) is proposed. Firstly channels are partitioned into finite states, then codebooks corresponding to each state are constructed, which are used to quantize channels transferred from corresponding states. Further, the state transition function is designed to ensure the synchronization between transmitter and receiver. The proposed algorithm can achieve improved performance with the same feedback load compared with classical memoryless channel quantizer without consideration of the influence of time correlation. Simulation results verify the effectiveness of the proposed algorithm.

Prior studies on limited feedback (LFB) beamforming in multiple-antenna orthogonal frequency division multiplexing (OFDM) have resorted to Monte-Carlo simulations to evaluate the system performance. This letter proposes a novel analytical framework, based on which the averaged signal-to-noise ratio and the ergodic capacity performance of clustering-based LFB beamforming in multiple-antenna OFDM systems are studied. Simulations are also provided to verify the analysis.

A multiple-antenna receiving and combining scheme is proposed for high-data-rate transmitted-reference (TR) Ultra-Wideband (UWB) systems. The nonlinearity of the inter-symbol interference (ISI) model is alleviated via simple antenna combining. Under the simplified ISI model, frequency domain equalization (FDE) is adopted and greatly reduces the complexity of the equalizer. A simple estimation algorithm for the simplified ISI model is presented. Simulation results demonstrate that compared to the single receive antenna scheme, the proposed method can obtain a significant diversity gain and eliminate the BER floor effect. Moreover, compared to the complex second-order time domain equalizer, FDE showed better performance robustness in the case of imperfect model estimation.

In spatial multiplexing systems using multiple antennas, the error-rate performance is heavily dependent on the residual channel estimation error. In this letter, we propose a design method that uses the genetic algorithms to optimize training sequences for accurate channel estimation.