Design and analysis of detection algorithms for MIMO wireless communication systems

Abstract

The increasing demand for high-mobility and high data rate in wireless

communications results in constraints and problems in the limited radio spectrum,

multipath fading, and delay spread.

The multiple-input multiple-output (MIMO) system has been generally

considered as one of the key technologies for the next generation wireless

communication systems. MIMO systems which utilize multiple antennas in both

the transmit side and the receive side can overcome the abovementioned

challenges since they are able to increase the channel capacity and the spectrum

usage efficiency without the need for additional channel bandwidth.

The detection algorithm is a big bottleneck in MIMO systems. Generally, it is

expected to fulfill two main goals simultaneously: low computational complexity

and good error rate performance. However, the existing detection algorithms are

either too complicated or suffering from very bad error-rate performance.

The purpose of this thesis is to comprehensively investigate the detection

algorithms of MIMO systems, and based on that, to develop new methods which

can reduce the computational complexity while retain good system performance.

Firstly, the background and the principle of MIMO systems and the previous work

on the MIMO decoding algorithms conducted by other researchers are thoroughly

reviewed. Secondly, the geometrical analysis of the signal detection is

investigated, and a geometric decoding algorithm which can offer the optimum

BLER performance is proposed. Thirdly, the semidefinite relaxation (SDR)

detection algorithms are extended to high-order modulation MIMO systems, and a

novel SDR detector for 256-QAM constellations is proposed. The theoretical

analysis on the tightness and the complexity are conducted. It demonstrates that

the proposed SDR detector can offer better BLER performance, while its

complexity is in between those of its two counterparts. Fourthly, we combine the

SDR detection algorithms with the sphere decoding. This is helpful for reducing

the computational complexity of the traditional sphere decoding since shorter

initial radius of the hyper sphere can be obtained. Finally, the novel

lattice-reduction-aided SDR detectors are proposed. They can provide

near-optimum error rate performance and achieve the full diversity gain with very

little computational complexity added compared with the stand-alone SDR

detectors.