ABSTRACT

Cognitive radio technology introduces a revolutionary wireless communication network. This technology is employed to increase frequency spectrum efficiency of the limited spectral resources. Efficient resource allocation methodology has been a challenge to a good system performance of cognitive radio network. In this dissertation an improved power and sub channel resource allocation scheme is developed to ascertain the performance of a multi-hop relay cooperative communication system using orthogonal frequency division multiplexing (OFDM) technique. The cooperative diversity protocol employed at the relay terminal (Base Station) is the Amplify and forward (AAF) & decode and amplify (DAF) relaying protocols. The information is transmitted over a wireless Raleigh fading channel. The distance and number of relays are variable parameters which affect the performance and bit error rate (BER) of the secondary users (SU). However, comparing the result of the LOME model with theoretical value and another model it shows a reasonable agreement with the theoretical value than CDD and upper bound model. Since the bits’ error rate gradually reduced and tends to zero for power and subchannel simulation. The LOME model using DAF protocol at cognitive relays and subchannel scheme were implemented and results are validated by MATLAB simulation and statistics. Therefore, we propose an allocation scheme that maximizes the energy efficiency of the system while minimizing the BER of the network. Results validated shows that the mean square error (MSE) values for Figure 4.5, Figure 4.7, Figure 4.8 and Figure 4.9 has a value of 0.0000. Values closer to zero are better. The highest MSE value for the LOME model is 0.0005 compared with the Conventional differential detection (CDD) model which has a value as high as 0.0011. The MSE shows that the LOME model has a far better estimation of the theoretical model than the CDD model. The test results also show clearly that the root mean square error (RMSE) values for the LOME model are far lesser than the CDD model. The lowest value for the LOME model is seen as 0.0010 as in Figure 4.5 analysis compared to the CDD model of about 0.0167 as in Figure 4.3. Lower values of RMSE give a more accurate prediction model. We also have higher spread of median absolute deviation (MAD) in the CDD model than the LOME model. The highest value of 0.128 as in Figure 4.1 and lowest value of 0.06 as in Figure 4.5 analysis all occurred at the LOME model. The LOME model achieves about 62.5% efficiency compared with the theoretical model in terms of transmit power and BER. These validations proved that the LOME model gives a better BER and a better prediction of the theoretical scheme than the CDD model. These will generally result to a more efficient and robust cognitive radio network.