Design and Analysis of Cooperative Communications Networks Using Game Theory

Connectivity and high transmission rates are desired in wireless networks to offer reliable and high quality services to users through broadband applications. The wireless services cover a wide range of broadband applications such as wireless internet, video streaming, and mobile TV. However, current wireless technologies cannot completely support the growing demand for these high data rate applications due to the limited available wireless resources in terms of frequency bandwidth and transmission power. Moreover, retaining connectivity and an acceptable level of quality for network users in urban and rural areas requires a huge investment to establish more network radio stations. The higher investment cost might increase the cost of service for customers, which is not desired for service providers. This proposed research considers this challenging issue and proposes a novel software-based technique to improve network connectivity and enhance resource utilization efficiency while imposing minimal changes to the existing network infrastructure at the hardware level. The idea is to exploit the high computational capability of handsets and develop more intelligent and flexible cooperative algorithms to secure connectivity. One important challenge in wireless networks is to maintain quality of service for network users, when the quality of communication links drop due to the undesired noise and interference effects. To address this challenge, the proposed solution in this dissertation involves a cognitive cooperation algorithm to provide connectivity to the far away users by forming a temporary multi-hop relaying chain through other network users. Employing cooperative communication yields various advantages including higher link reliability, enhanced data transmission performance, and lower energy consumption. However, transmission protocols will be more complex. Different aspects of this algorithm including packet forwarding, optimal resource usage and relaying schemes are studied and proper game theoretical solutions are provided. Using game theory as an advanced optimization tool enables us to shift the network control and resource allocation algorithms from a central controller to a distributed version among cognitive network users. A distributed decision making policy provides suboptimal performances with the advantages of high reliability and robustness to central controller failure