Open AccessDistributed allocation of subcarrier, power and bit‐level in multicell orthogonal frequency‐division multiple‐access networks
Author(s) -
Fathi Mohammad,
Karipidis Eleftherios
Publication year - 2014
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2013.0463
Subject(s) - subcarrier , orthogonal frequency division multiple access , computer science , division (mathematics) , bit (key) , orthogonal frequency division multiplexing , power (physics) , frequency divider , telecommunications , electronic engineering , computer network , mathematics , arithmetic , engineering , channel (broadcasting) , physics , quantum mechanics , power dividers and directional couplers
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.