Prior studies have shown that the performance of amplify-and-forward (AF) relay systems can be considerably improved by using multiple antennas and low complexity linear processing at the relay nodes. However, there is still a lack of performance analysis for the cases where the processing is based on limited feedback (LFB). Motivated by this, we derive the closed-form expression of the outage probability of AF relay systems with LFB beamforming in this letter. Simulation results are also provided to confirm the analytical studies.

Recently, it has been shown in the literature that in a relaying network utilizing multiple relay precoding techniques, the signal-to-noise ratio (SNR) at each destination node will scale linearly with the number of relays K, which is referred to as the distributed array gain (DAG) K. In this paper, we focus on the performance of multiple relay precoding based on limited channel state information (CSI) feedback, which is different from the prior studies that assume perfect CSI at each of the relay nodes. Our analysis shows that the conventional limited feedback scheme fails to obtain the DAG K, which is a consequence of the phase ambiguity introduced by the channel quantization function. Based on the theoretical analysis, we propose a novel feedback and precoding procedure, and prove that the proposed procedure can obtain the DAG K with only one additional feedback bit for quantizing each relay-destination channel compared with the conventional scheme. Simulation results verify that with the proposed procedure, the SNR performance is effectively improved when the number of relays K is small, and scales linearly with K in relatively large K regime.

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.

In this letter, a dual-hop wireless communication network with opportunistic amplify and forward (O-AF) relay is investigated over independent and non-identically distributed Nakagami-m fading channels. Employing Maclaurin series expansion around zero to derive the approximate probability density function of the normalized instantaneous signal-to-noise ratio (SNR), the asymptotic symbol error rate (SER) and outage probability expressions are presented. Simulation results indicate that the derived expressions well match the results of Monte-Carlo simulations at medium and high SNR regions. By comparing the O-AF with all AF relaying analyzed previously, it can be concluded that the former has significantly better performance than the latter in many cases.

In this letter, we derive a lower bound on the diversity multiplexing tradeoff (DMT) in multiple-input multiple-output (MIMO) nonorthogonal amplify-and-forward (NAF) cooperative channels with resolution-constrained channel state feedback. It is shown that power control based on the feedback improves the DMT performance significantly in contrast to the no-feedback case. For instance, the maximum diversity increase is exponential in K with K-level feedback.

In this letter, we analyze the performance of limited feedback beamforming in a distributed antenna system. We propose a novel codebook design scheme to maximize a lower bound of the averaged effective signal-to-noise ratio (SNR), which is a function of the power of the signal and noise, the number of antennas, and the number of total feedback bits for characterizing the quantized channel vector. Simulations verify that the proposed scheme can provide effective capacity improvement.

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.

Antenna selection is a practical way to decrease system complexity and the hardware cost of radio frequency (RF) chains in multiple input multiple output (MIMO) system. In this study, we give a simple characterization of the optimal diversity and multiplexing tradeoff (DMT) curve of the MIMO system with antenna subset selection at both the transmitter and the receiver for Rayleigh fading channel.

In this paper, we consider an amplify-and-forward (AF) relay network where a source node transmits information to a destination node through the cooperation of multiple relay nodes. It is shown in prior works that the outage behavior and average throughput of the selection AF (S-AF) scheme where only the best relay node is chosen to assist can outperform the conventional all-participate AF (AP-AF) scheme. Assuming multiple antennas at the destination node and single antennas at other nodes in this paper, we propose a relay selection scheme according to the criterion of maximizing receive signal to noise ratio (SNR), where a group of relays is chosen to assist in the transmission simultaneously in a manner similar to cyclic delay diversity (CDD). Compared with S-AF, the proposed scheme achieves better outage behavior and average throughput. It can be seen from simulation results that the performance improvement of symbol error rate (SER) is significant compared with S-AF.