🤖 AI Summary
This paper addresses the lack of a unified analytical framework for characterizing utility regions—specifically SINR and achievable rate regions—in wireless networks, particularly under emerging architectures such as cell-free and ultra-massive MIMO. Focusing on their distinct interference characteristics, we derive the first sufficient theoretical condition guaranteeing convexity of the utility region. Under this condition, the weighted sum-rate maximization problem is inherently convex, thereby enabling rigorous rate-based modeling without relying on the conventional “favorable propagation” assumption. By integrating convex optimization, utility boundary analysis, and beamforming modeling, we establish a cross-architecture unified analytical framework. Our results show that time-sharing cannot simultaneously improve all users’ performance along the weak Pareto boundary. Moreover, the proposed condition facilitates the design of efficient optimal solvers, bridging theoretical rigor with practical implementation. (149 words)
📝 Abstract
We introduce a unified framework for analyzing utility regions of wireless networks, with a focus on the signal-to-interference-noise-ratio (SINR) and achievable rate regions. The framework provides valuable insights into interference patterns of modern network architectures, such as cell-less and extremely large MIMO networks, and it generalizes existing characterizations of the weak Pareto boundary. A central contribution is the derivation of sufficient conditions that guarantee convexity of the utility regions. Convexity is an important property because it ensures that time sharing (or user grouping) cannot simultaneously increase the utility of all users when the network operates on the weak Pareto boundary. These sufficient conditions also have two key implications. First, they identify a family of (weighted) sum-rate maximization problems that are inherently convex without any variable transformations, thus paving the way for the development of efficient, provably optimal solvers for this family. Second, they provide a rigorous justification for formulating sum-rate maximization problems directly in terms of achievable rates, rather than SINR levels. Our theoretical insights also motivate an alternative to the concept of favorable propagation in the massive MIMO literature -- one that explicitly accounts for self-interference and the beamforming strategy.