A modified ML decision for the relay-based cooperative communication system using complex field network coding

In this paper, we propose a modified maximum likelihood (ML) decision for a relay-based cooperative communication system using complex field network coding (CFNC). Since the traditional uncoded relay network which is wirelessly connected by inband within the donor cell causes interference during simultaneous transmissions through the intermediate relay, each signal in traditional uncoded relay network is transmitted over several time slots. Therefore, it has to spend a lot of time communicating. To overcome this inherent limitation, CFNC is considered because it has an advantage of minimizing the number of required time slots for information exchange. However, for detecting transmitted symbols from each node, the ML decision which has an exponential increase in the computational complexity with the number of symbol is used. Therefore, we propose a modified ML decision based on the symbol detection process using the channel power, which not only can reduce the computational complexity but also maintain the same bit error rate (BER) performance compared with the conventional ML decision. By extensive computer simulation in various channel environments, we verify that the modified ML decision is attractive and suitable for the relay-based cooperative communication system using CFNC.