-Fair Power Allocation in Spectrum-Sharing Networks

C Guo, Y Zhang, M Sheng, X Wang… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
C Guo, Y Zhang, M Sheng, X Wang, Y Li
IEEE Transactions on Vehicular Technology, 2015ieeexplore.ieee.org
To efficiently trade off system sum-rate and link fairness, this paper is dedicated to
maximizing the sum of α-fair utility in spectrum-sharing networks, where multiple interfering
links share one channel. In the literature, three special cases, including α= 0 (sum-rate
maximization), α= 1 (proportional fairness), and α=∞(max-min fairness), have been
investigated; the complexity for cases 1<; α<;∞ and 0<; α<; 1 is still unknown. In this paper,
we prove that the problem is convex when 1<; α<;∞ and is NP-hard when 0<; α<; 1. To deal …
To efficiently trade off system sum-rate and link fairness, this paper is dedicated to maximizing the sum of α-fair utility in spectrum-sharing networks, where multiple interfering links share one channel. In the literature, three special cases, including α = 0 (sum-rate maximization), α = 1 (proportional fairness), and α = ∞ (max-min fairness), have been investigated; the complexity for cases 1 <; α <; ∞ and 0 <; α <; 1 is still unknown. In this paper, we prove that the problem is convex when 1 <; α <; ∞ and is NP-hard when 0 <; α <; 1. To deal with the latter case, we transform the objective function and represent it by the difference of two concave functions (D.C.). Then, a power allocation algorithm is proposed with fast convergence to a local optimal point. Simulation results show that the proposed algorithm can obtain global optimality in two-link cases when 0 <; α <; 1. In addition, we can get a flexible tradeoff between sum-rate and fairness in terms of Jain's index by adjusting α.
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