Research On The Diversity-Multiplexing Tradeoff Performance And Antenna Selection Techniques Of The Multiple Antenna System

The multiple antennas (MIMO: Multiple Input Multiple Output) technology of wireless communications is advanced technology applying multiple antennas on both the transmitter and the receiver. It provides an optimal key solution for improving the capacity or the reliability of the wireless communications.Multiple antennas can be used either for increasing the amount of diversity or the number of degrees of freedom in wireless communication system, but there is a fundamental tradeoff between how much of each scheme can get. Most space time schemes aim at maximizing either of them, and how to evaluate the diversity-based and the multiplexing-based schemes is a problem.Multiple antennas system typically implies the increased cost as compared with the single antenna system. So it is worth studying for how to decrease the cost with unchanged performance. Except for the high efficient space time coding techniques, the antenna selection (AS) technique is proposed. Antenna selection, as it is named, is to select some antennas out of the total antenna array according to a certain criterion. It has been shown to be a low cost and low complexity alternative to mitigate the problem of the multiple antennas system.This paper has made deep research in the diversity-multiplexing tradeoff performance of the multiple antennas system and the AS techniques. The main contributions are as following:1) A parallel concatenated space time trellis codes (PC-STTC) scheme is proposed. It can achieve the tradeoff between the performances and the complexity of space time trellis codes. Simulation is provided to verify this scheme, and the EXIT (Extrinsic Information Transfer) chart is given to analyze its performance. Meanwhile, this paper proposes and verifies the scheme combing the space time turbo trellis codes and the AS techniques. A kind of space time scheme using the only one cycle (OOC) interleaver is introduced. The iterative receiver is designed and the performance simulation under different channels is done.2) This paper analyzes the tradeoff performance of the linear dispersive codes (LDC) over both the block fading and the fast fading channels. LDC, as a kind of space time scheme, was proved to be able to achieve the favorable diversity properties while still guaranteeing the channel capacity. In order to provide a more complete evaluation of the achievable performance for the LDCs scheme over multiple antenna channels, this paper makes an effort to investigate on the diversity-multiplexing tradeoff performance of the LDCs scheme over both the block fading and the fast fading channels. Results indicate that the LDCs scheme can achieve the optimal diversity-multiplexing tradeoff over block fading channels. For fast fading channels the analysis shows that LDCs can achieve both the space diversity and the time diversity simultaneously.3) The diversity-multiplexing tradeoff performance for the complex multivariate t (CMT) channel model is provided. The diversity-multiplexing tradeoff function provides a complete view to evaluate the performance of multiple antenna schemes for a given multiple antennas channel. However, most of the previous work considers the richly scattered Rayleigh fading channel environment. Based on the severely fading CMT channel model, this paper makes efforts to derive the diversity-multiplexing tradeoff function. It is found that the CMT channel tradeoff performance is specially related to the maximum eigenvalue of the channel matrix and the channel model's degrees of freedom (CMDF), which represents the extent of the fading. For the infinite CMDF, the diversity-multiplexing tradeoff function coincides with the existing result for the richly scattered Rayleigh fading channel.4) A new antenna selection algorithm for MIMO wireless systems is proposed. The objective of the antenna selection is to find the optimal antenna subset which can provide better capacity or performance. In this paper, the modified Tanimoto coefficient is used to compare the similarity of the rows/columns of the channel matrix. Based on the calculated similarity, the proposed algorithm chooses the antenna subset, which has the maximum product of dissimilarity and Frobenius norm. The proposed algorithm requires low computational complexity as to the optimal selection but with comparative outage capacity and average signal to noise ratio (SNR) performance. It can improve both the outage capacity and the average SNR as compared to the random selection.5) The theoretical performance for the antenna selection system with channel estimation error is derived. The error performance analysis is important for the design of the AS system. However, most of the research in the literature assumes ideal channel information at the receiver to simplify the problem. This paper quantifies the effect of imperfect channel estimation on multiple antenna selection system. And the symbol error rate (SER) performance is derived using two different methods. The simulation results show that the theoretic result matches the system performance with whether ideal or noisy channel information. Numerical results show that in the lower SNR region, the system performance depends more on the quality of channel estimation than on the number of the transmit antenna. Based on the theoretical analysis, a novel power allocation scheme is proposed. The proposed power allocation scheme can achieve about 3dB gain as to the equal power allocation scheme. And it suffers only 1dB performance loss as compared with the ideal channel information situation. This shows that adapting a reasonable power allocation scheme will improve the system performance dramatically.