In this thesis, different approaches for improving the bandwidth efficiency of Multiple Access Channels (MAC) have been proposed. Such improvements can be achieved with methods that use network coding, or with methods that implement successive decoding. Both of these two methods have been discussed here.
Under the first method, two novel schemes for using network coding in cooperative networks have been proposed. In the first scheme, network coding generates some redundancy in addition to the redundancy that is generated by the channel code. These redundancies are used in an iterative decoding system at the destination. In the second scheme, the output of the channel encoder in each source node is shortened and transmitted. The relay, by use of the network code, sends a compressed version of the parts missing from the original transmission. This facilitates the decoding procedure at the destination. Simulation based optimizations have been developed. The results indicate that in the case of sources with non-identical power levels, both scenarios outperform the non-relay case.
The second method, involves a scheme to increase the channel capacity of an existing channel. This increase is made possible by the introduction of a new Raptor coded interfering channel to an existing channel. Through successive decoding at the destination, the data of both main and interfering sources is decoded.
We will demonstrate that when some power difference exists, there is a tradeoff between achieved rate and power efficiency. We will also find the optimum power allocation scenario for this tradeoff. Ultimately we propose a power adaptation scheme that allocates the optimal power to the interfering channel based on an estimation of the main channel's condition.
Finally, we generalize our work to allow the possibility of decoding either the secondary source data or the main source data first. We will investigate the performance and delay for each decoding scheme. Since the channels are non-orthogonal, it is possible that for some power allocation scenarios, constellation points get erased. To address this problem we use constellation rotation. The constellation map of the secondary source is rotated to increase the average distance between the points in the constellation (resulting from the superposition of the main and interfering sources constellation.) We will also determine the optimum constellation rotation angle for the interfering source analytically and confirm it with simulations
