Dynamic Radio Resource Management for Advanced Wireless Communication Systems

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The main theme of the research program is radio resource management (RRM) for advanced wireless communication systems. For a wireless network operating in a fading environment, power and bandwidth are precious radio resources that need detailed and careful planning. Reducing power consumption while satisfying a targeted Quality of Service (QoS) requirement leads to an enlarged overall capacity for the communication system and a prolonged battery life for the communication devices. In this proposal, we will investigate the RRM problems in wireless communication systems involving Cognitive Radio (CR), Multiple-input Multiple-output (MIMO), Orthogonal Frequency Division Multiplexing (OFDM), and energy harvesting green communication techniques. With the evolution to a more sophisticated wireless communication system, the issues of optimal RRM problems have become ever so important to achieve an overall optimal system design. Water-filling (WF) has been an important algorithm to solve RRM problems in fading channels. With water-filling, more power is allocated to the channels with higher gains to maximize the system throughput. A conventional way that utilizes the WF algorithm (CWF) to solve the optimal power allocation problem is to solve the Karush-Kuhn-Tucker (KKT) conditions, and then find the water-level(s) and the solutions. Recently, we proposed a Geometrically approached WF algorithm (GWF). Comparing with the CWF approach, GWF provides a closed form solution to the power allocation problem and avoids the computational complexity of solving a set of non-linear equations. In addition, we have demonstrated that GWF can be extended to solve more generalized and hence more complicated RRM problems. In our most recent research, we explored this beneficial property even further by demonstrating a set of recursive power allocation algorithms for energy harvesting green communication systems in fading channels. The proposed research is built upon the outcomes of our earlier research, i.e. to investigate the water-filling mechanism and to develop a series of optimal RRM algorithms to accomplish the dynamic and optimal features for different system settings. We will focus on three main research topics in the proposal: 1) optimal power allocation algorithms for wireless communication with energy harvesting nodes in CR networks; 2) dynamic RRM optimization for energy harvesting and power grid coexisting systems with fair power allocation constraints; and 3) optimal algorithms for OFDM wireless networks with CRs. The long-term research objectives are to extend the proposed algorithms to multi-user cases, and further to real-time resource allocation algorithms. Both will be effectively utilized in practice. And they will push the performance boundary of the current state of art technology. The proposed research builds on the success of water-filling algorithms, and more generally, the application of optimization theory in the field of communications and signal processing. This research will propel the associated academic research and advance this technological innovation to the next level. The successful completion of these research projects will contribute to the overall growth of the fundamental knowledge in the field of multi-user information theory and push the engineering frontier of the next-generation wireless communication systems.