Optimization of V-Blast and C-Blast Using Genetic Algorithm

Abstract

Multiple Input Multiple Output (MIMO) systems have been extensively studied in the context of wireless communications, promising both increased capacity and link level reliability. MIMO systems uses an array of transmit and receive antennas for enormous gains in spectral efficiency by exploiting a rich multipath fading environment. Following the proposal by Foschini at Bell Labs, a family of architectures emerged for systems employing multiple antenna arrays at transmit and receive end, collectively known as Bell Labs Layered Space-Time (BLAST) architectures. BLAST (Bell Labs Layered Space-Time) is a multiple antenna communication scheme to improve the performance of wireless communication by increasing data rate. This dissertation gives a proposed method to increase the throughput by 10% if we use the combination of V-BLAST and C-BLAST. This dissertation reviews the essential aspects of two of the best known members of the family, namely C-BLAST, V-BLAST. V-BLAST improves the performance at the cost of increased computational complexity. In V-BLAST, instead of jointly detecting all the transmit signals, the detection is done iteratively. At each symbol time, for each subcarrier, it first detects the strongest layer (depending on the channel matrix) and then cancels the effect of this strongest layer from each of the received signals, considered as interference. The detection continues with the strongest remaining layer, and so on. An extension of the open-loop V-BLAST transmission structure referred to as the closed-loop V-BLAST. The closed-loop V-BLAST differs from the open-loop V-BLAST in respect that there exists a feedback channel that enables the receiver to send to the transmitter the optimized transmit adaptation based on the instantaneous channel realization, which is assumed to be perfectly known at the receiver. Further, improvement can be done in the performance characteristics like bit error rate , SNR and power allocation for V-BLAST and C-BLAST by using genetic algorithms which based upon creation of top point in the population which reaches an optimum solution by creating a population of points at every iteration. So if genetic algorithm is used, throughput increases and bit error rate decreases. On the other hand if genetic algorithm is not used in combination with V- BLAST then throughput will decrease and iv bit error rate will go high. Finally, discussion of results has been explained in end of the dissertation.