Dynamic Radio Resource Management for Advanced Wireless Communication Systems

该研究计划的主题是先进无线通信系统的无线电资源管理（RRM）。对于在衰落环境中运行的无线网络，功率和带宽是宝贵的无线电资源，需要详细而仔细的规划。在满足目标服务质量（QoS）要求的同时降低功耗，可以扩大通信系统的总体容量，延长通信设备的电池寿命。在本提案中，我们将研究无线通信系统中的RRM问题，包括认知无线电（CR），多输入多输出（MIMO），正交频分复用（OFDM）和能量收集绿色通信技术。随着无线通信系统向更复杂的方向发展，优化RRM问题对于实现系统的整体优化设计变得越来越重要。**水填充（WF）是解决衰落信道中RRM问题的重要算法。充水时，将更多的功率分配给增益较高的通道，使系统吞吐量最大化。利用WF算法（CWF）求解最优功率分配问题的传统方法是先求解Karush-Kuhn-Tucker （KKT）条件，然后求出水位及其解。最近，我们提出了一种几何逼近WF算法（GWF）。与CWF方法相比，GWF方法为电力分配问题提供了一个封闭的解，避免了求解一组非线性方程的计算量。此外，我们已经证明，GWF可以扩展到解决更广义的、因此更复杂的RRM问题。在我们最近的研究中，我们通过展示一套用于在衰落信道中收集能量的绿色通信系统的递归功率分配算法，进一步探索了这一有益特性。**本研究是建立在前期研究成果的基础上，即研究充水机理，并开发一系列最优RRM算法，以实现不同系统设置下的动态和最优特征。我们将在提案中重点研究三个主要课题：1)CR网络中具有能量收集节点的无线通信的最优功率分配算法；2)具有公平分配约束的能量收集与电网共存系统动态RRM优化；3)带cr的OFDM无线网络的最优算法。长期的研究目标是将所提出的算法扩展到多用户场景，并进一步扩展到实时资源分配算法。两者都将在实践中得到有效利用。它们将推动当前最先进技术的性能边界。提出的研究建立在充水算法的成功基础上，更广泛地说，是优化理论在通信和信号处理领域的应用。这项研究将推动相关的学术研究，并将这项技术创新推向一个新的水平。这些研究项目的成功完成将有助于全面发展多用户信息理论领域的基础知识，并推动下一代无线通信系统的工程前沿。

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.