2021/12/07 by Imran Ahmed, Ahmed, I. Zakir, Hamid R. Sadjadpour +3
Computer Science · Engineering · #Cooperative Communication and Network Coding #FOS: Computer and information sciences #FOS: Electrical engineering #Information Theory (cs.IT) #Optimization and Packing Problems #Signal Processing (eess.SP) #electronic engineering #graph theory and CDMA systems #information engineering
paper · pdf · doi:10.48550/arxiv.2112.03512
openalex publication_date 2021/12/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We consider a class of resource allocation problems given a set of unconditional constraints whose objective function satisfies Bellman's optimality principle. Such problems are ubiquitous in wireless communication, signal processing, and networking. These constrained combinatorial optimization problems are, in general, NP-Hard. This paper proposes two algorithms to solve this class of problems using a dynamic programming framework assisted by an information-theoretic measure. We demonstrate that the proposed algorithms ensure optimal solutions under carefully chosen conditions and use significantly reduced computational resources. We substantiate our claims by solving the power-constrained bit allocation problem in 5G massive Multiple-Input Multiple-Output receivers using the proposed approach.