Distributed allocation of subcarrier, power and bit‐level in multicell orthogonal frequency‐division multiple‐access networks. Issue 6 (1st April 2014)

• Record Type: Journal Article
• Authors: Fathi, Mohammad; Karipidis, Eleftherios
• Is Part Of: IET communications. Volume 8:Issue 6(2014)
• Page Start: 781
• Page End: 788
• Publication Date: 2014-04-01
• Subjects: adaptive filters -- channel allocation -- channel estimation -- communication complexity -- frequency allocation -- frequency division multiple access -- integer programming -- iterative methods -- linear programming -- nonlinear programming -- OFDM modulation -- radio receivers; distributed subcarrier allocation -- power allocation -- bit level allocation -- orthogonal frequency division multiple access -- adaptive spectrum allocation -- adaptive frequency reuse -- discrete level rate allocation -- joint allocation problem -- centralised nonlinear mixed integer program -- subcarrier channel gain estimation -- linear complexity -- base station perform rate -- receiver allocation per subcarrier -- concurrent iteration -- filtering method -- branch‐and‐cut solvers -- linear MIP -- iterative waterfilling algorithm; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2013.0463
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : The downlink of multicell orthogonal frequency‐division multiple‐access (OFDMA) networks is studied, and the adaptive allocation of spectrum, power and rate is addressed. The authors consider networks with adaptive frequency reuse and discrete‐level rates. Initially, the joint allocation problem is formulated as a centralised non‐linear mixed‐integer program (MIP), which is computationally intractable to solve optimally for practical problem sizes. Then, the capability of the receivers is exploited to estimate the subcarrier channel gains and the joint allocation problem is accordingly decomposed into subproblems, each of which is solved by a different base station with linear complexity. In the proposed iterative algorithm, the base stations perform rate and receiver allocation per subcarrier, with concurrent iterations. A filtering method is introduced to further decrease the algorithm complexity. Furthermore, for benchmarking purposes, the authors transform the original non‐linear MIP to a linear MIP and find the optimal solution by means of standard branch‐and‐cut solvers. The merit of the proposed algorithm is demonstrated with numerical comparisons of its performance against the solutions of the linear MIP and the iterative waterfilling algorithm.