Dynamic Transmit Antenna Shuffling Scheme for Hybrid Multiple-input Multiple-output in Layered Architecture

Download or read book Dynamic Transmit Antenna Shuffling Scheme for Hybrid Multiple-input Multiple-output in Layered Architecture written by Jin Hui Chong and published by . This book was released on 2010 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The wireless evolution has been stimulated by an explosive growing demand for a wide variety of high quality of services in voice, video, and data. This rigorous demand has made an impact on current and future wireless applications, such as digital audio broadcasting and video streaming. In particular, one of the main challenges in the single-input single-output (SISO) wireless communication is a wireless channel that suffers from numerous physical impairments due to multipath propagation. Besides, the constraints posed by limited power, capacity and scarce spectrum make the design of SISO reliability challenging. The idea of multiple antennas at the transmitter and receiver has introduced multiple-input multiple-output (MIMO) system, which increases robustness to the effect of multi-path fading provides higher data rates without consuming extra bandwidth and power. In this thesis, three major advances on multiple-input multiple-output (MIMO) systems are presented. First, V-BLAST/STBC transceiver scheme, which incorporates the vertical Bell-labs layered space-time (V-BLAST) and Alamouti's space-time block codes (STBC) is considered. This transceiver scheme is able to enhance the MIMO wireless communication system performance in terms of bit error rate (BER) by achieving spatial diversity and multiplexing gain simultaneously. A new detection algorithm based on QR decomposition, denoted as LC-QR, is proposed. The QR decomposition is a common signal processing technique for MIMO detection. The computational complexity (total number of arithmetic operations) of proposed LC-QR algorithm is significantly lower than the conventional QR decomposition, zero-forcing (ZF) and minimum mean square error (MMSE) detection algorithm. Finally, the performance of V-BLAST/STBC transceiver scheme with proposed LC-QR algorithm is compared with other MIMO systems, such as V-BLAST and orthogonal space-time block codes. The BER performance of V-BLAST/STBC scheme is better than V-BLAST scheme while the system capacity of V-BLAST/STBC scheme is higher than orthogonal space time block codes. The second part contributes to the field of dynamic transmit antenna shuffling scheme for MIMO system to maximize the system capacity and reducing BER. Channel state information (CSI) is assumed to be known by the transmitter via a dedicated feedback channel. Dynamic transmit antenna shuffling scheme improves the performance of MIMO by selecting the appropriate pairs of antennas at transmitter based on the CSI from receiver. Two dynamic transmit antenna shuffling schemes, namely 'Optimal' and 'Max STBC', are proposed to enhance the V-BLAST/STBC transceiver scheme with LC-QR proposed in the first part. The 'Optimal' dynamic transmit antenna shuffling scheme with low complexity feedback requirements improves the BER performance significantly with a gain of 2 dB at BER of 10-3 compared to the V-BLAST/STBC transceiver scheme without transmit antenna shuffling capability. Besides, the 'Max STBC' dynamic transmit antenna shuffling scheme increases the system capacity of V-BLAST/STBC transceiver scheme for 4 %. In the third part, an implementation of a multi-layered space-frequency orthogonal frequency division multiplexing transceiver scheme (MLSF-OFDM) that integrates SF-OFDM with V-BLAST OFDM in a layered architecture has been considered. The MLSF-OFDM system is modeled over Monte-Carlo time-variant channel model with different maximum Doppler frequency. Special training sequences are used in the least square (LS) channel estimation method to obtain a desirable crest-factor, which is defined as the ratio of peak amplitude of waveform to the root mean square (RMS) value of the waveform, of the transmitted training signal and eliminate the influence of inter-symbol interference (ISI) on the channel estimation performance. A fast QR decomposition detection algorithm, denoted as FAST-QR, is proposed for MLSF-OFDM. It is shown that the computational complexity of proposed FAST-QR detection algorithm is approximately 48 % lower than the conventional QR decomposition detection algorithm. Besides, the result shows that the BER performance of proposed FAST-QR detection algorithm degrades marginally compared to ZF with successive interference cancellation (SIC-ZF) detection algorithm.