无线通信资源配置中的优化问题与方法

Many problems arising from wireless communication system design can be formulated into optimization problems. On the one hand, these optimization problems are often highly nonlinear, and thus generally difficult to solve. On the other hand, they have their own special structures, such as hidden convexity and separability. Designing efficient optimization algorithms to solve these problems based on their special structure has been a hot research topic in recent years. In this paper, we focus on optimization methods for resource allocation problems in wireless communication system design. Taking optimization theories and algorithms as the main line, we introduce their applications in solving resource allocation problems, including how conic programming reveals the hidden convexity in specific non-convex problems, how Lagrangian duality helps to characterize the structure of their optimal solutions, how sparse optimization and integer programming techniques help to formulate the related problems, and how semidefinite relaxation, alternating optimization, and fractional programming help to design efficient algorithms. Finally, we give a prospect of some future research directions and the key problems in wireless communication system design.