2015/02/04 by Piotr Wiecek, Piotr Więcek, Wiecek, Piotr +7
Computer Science · Engineering · Mathematics · #Advanced MIMO Systems Optimization #Advanced Wireless Network Optimization #Cognitive Radio Networks and Spectrum Sensing #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Information Theory (cs.IT) #Networking and Internet Architecture (cs.NI) #Wireless Communication Networks Research #cs.GT #cs.IT #cs.NI #math.IT
paper · pdf · doi:10.48550/arxiv.1502.01157
9 pages, 6 figures
arxiv created 2015/02/04 · openalex publication_date 2015/02/04 · arxiv updated 2015/02/05 · openalex created_date 2022/10/04 · openalex updated_date 2026/07/28
Enabling coordination between products from different vendors is a key characteristic of the design philosophy behind future wireless communication networks. As an example, different devices may have different implementations, leading to different user experiences. A similar story emerges when devices running different physical and link layer protocols share frequencies in the same spectrum in order to maximize the system-wide spectral efficiency. In such situations, coordinating multiple interfering devices presents a significant challenge not only from an interworking perspective (as a result of reduced infrastructure), but also from an implementation point of view. The following question may then naturally arise: How to accommodate integrating such heterogeneous wireless devices seamlessly? One approach is to coordinate the spectrum in a centralized manner. However, the desired autonomous feature of future wireless systems makes the use of a central authority for spectrum management less appealing. Alternately, intelligent spectrum coordination have spurred great interest and excitement in the recent years. This paper presents a multi-level (hierarchical) power control game where users jointly choose their channel control and power control selfishly in order to maximize their individual energy efficiency. By hierarchical, we mean that some users' decision priority is higher/lower than the others. We propose two simple and nearly-optimal algorithms that ensure complete spectrum coordination among users. Interestingly, it turns out that the complexity of the two proposed algorithms is, in the worst case, quadratic in the number of users, whereas the complexity of the optimal solution (obtained through exhaustive search) is N!.