Capacity Enhancement of a MIMO Cognitive Radio System Using Water-Filling Strategy

The mobile communication systems will be differentiated by higher throughput, flexibility, and large combination of services in the future. Thus, the structure and configuration of wireless networks have begun to change rapidly. In the present situation, the aim is not only to provide data communication to mobile users, but also provide significant high capacity and data rate within the same bandwidths. There are optional schemes to meet these requirements like space time coding (STC), advance antenna system (AAS), multiple inputs and multiple outputs (MIMO) systems. The MIMO systems can be used for interference reduction, spatial multiplexing and diversity. There are many algorithms for MIMO system to increase the data rate and capacity of the channels. In this thesis, we evaluate the capacity of the MIMO system using water-filling solution as well as compare it with other systems like SISO, MISO and SIMO. The strategic choice of power allocation is based on Lagrange multiplier which provides the best power allocation under the fix value of water level to the sub channels. We noted that the proper power allocation to the sub channels can cause significant improvement in capacity for high data transmission. Our simulation results, when we applied water filling strategy over (2×2) MIMO system which shows the improvement by 1.3017 bps/Hz at SNR 0 dB as well as 1.74323 bps/Hz at 15 dB with 2 kW power budget. When we apply the water filling strategy over (4×4) MIMO system with the same 2 kW power budget, it provides a significant performance in capacity by 3.8321 bps/Hz enhancement at SNR 0 dB as well as the capacity improve 5.837 bps/Hz at SNR of 15 dB. Keywords: Multiple Input Multi Output (MIMO), Water Filling, Channel Capacity, Spectral efficiency, Signal to noise ratio (SNR).