Multi-Objective Signal Processing Optimization: The Way to Balance Conflicting Metrics in 5G Systems

摘要: The evolution of cellular networks is driven by the dream ubiquitous wireless connectivity: Any data service instantly accessible everywhere. With each generation networks, we have moved closer to this dream; first delivering access voice communications, then providing services, and recently a WiFi-like experience with wide-area coverage user mobility management. support for high rates has been main objective in recent years, as seen from academic focus on sum-rate optimization efforts standardization bodies meet peak rate requirements specified IMT-Advanced. In contrast, variety metrics/objectives are put forward technological preparations 5G networks: higher rates, improved uniform experience, reliability lower latency, better energy efficiency, lower-cost devices scalability number devices, etc. These multiple objectives coupled, often conflicting manner such that improvements one lead degradation other objectives. Hence, design future calls new tools properly handle existence tradeoffs between In article, provide review multi-objective (MOO), which mathematical framework solve problems (...) We survey basic definitions, properties, algorithmic MOO. This reveals how signal processing algorithms used visualize inherent conflicts performance objectives, thereby allowing network designer understand possible operating points balance an efficient satisfactory way. For clarity, case study massive MIMO.