Distributed inter-cell interference mitigation via joint scheduling and power control under noise rise constraints Academic Article uri icon


  • Consider the problem of joint uplink scheduling and power allocation. Being inherent in almost any wireless system, this resource allocation problem has received extensive attention. Yet, most common techniques either adopt classical power control, in which mobile stations are received with the same Signal-to-Interference-plus-Noise Ratio, or use centralized schemes, in which base stations coordinate their allocations. In this work, we suggest a novel scheduling approach in which each base station, besides allocating the time and frequency according to given constraints, also manages its uplink power budget such that the aggregate interference, "Noise Rise", caused by its subscribers at the neighboring cells is bounded. Our suggested scheme is distributed, requiring neither coordination nor message exchange between the base stations. We rigorously define the allocation problem under noise rise constraints. Inspired by the fact that under the noise-rise constraints, interference experienced by base stations is bounded and its variance is expected to be low, we suggested an approximation in which each base station assumes fixed interference. Under this approximation we formalize the joint scheduling and power control under the noise rise constraints as an optimization problem and characterize the optimal solution. For the special case of homogeneous deployment we give the optimal solution and derive an efficient iterative algorithm to achieve it. We then discuss a relaxed problem, where the noise rise is constrained separately for each sub-channel or resource unit. While sub-optimal, this view renders the scheduling and power allocation problems separate, yielding an even simpler and more efficient solution, while the essence of the scheme is kept. Via extensive simulations, we show that the suggested approach increases overall performance dramatically, with the same level of fairness and power consumption.

publication date

  • June 1, 2014