We consider the problem of jointly optimizing channel pairing, channel-user assignment, and power allocation  in a single-relay cooperative system with multiple channels and multiple users , under several common relaying strategies . Both weighted sum-rate and max-min rate are consideredas the optimization objective , and transmission power constraints are imposed on both individual transmitters and the aggregate over all transmitters. This joint optimization problem naturally leads to a mixed-integer program. Despite the general expectation that such problems are intractable, we construct an efficient algorithm to find an optimal solution, which incurs computational complexity that is polynomial in the number of channels and the number of users . The proposed solution is based on continuous relaxation, which usually only leads to heuristic or approximate solutions, but the rich structure in our problem renders it an exception. By observing the special structure of a three-dimensional assignment problem derived from the original problem, we show that the obtained solution is not only optimal, but also computationally efficient through judicious choices of the optimization trajectory . We further demonstrate through numerical experiments that the jointly optimal solution can significantly improve system performance over its suboptimal alternatives.
We consider the problem of jointly optimizing channel pairing, channel-user assignment, and power allocation , to maximize the weighted sum-rate, in a single-relay cooperative system with multiple channels and multiple users . Common relaying strategies are considered , and transmission power constraints are imposed on both individual transmitters and the aggregate over all transmitters. The joint optimization problem naturally leads to a mixed-integer program. Despite the general expectation that such problems are intractable, we construct an efficient algorithm to find an optimal solution, which incurs computational complexity that is polynomial in the number of channels and the number of users . We further demonstrate through numerical experiments that the jointly optimal solution can significantly improve system performance over its suboptimal alternatives.
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, to maximize the weighted sum-rate,
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, under several common relaying strategies . Both weighted sum-rate and max-min rate are consideredas the optimization objective
. Common relaying strategies are considered
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. The proposed solution is based on continuous relaxation, which usually only leads to heuristic or approximate solutions, but the rich structure in our problem renders it an exception. By observing the special structure of a three-dimensional assignment problem derived from the original problem, we show that the obtained solution is not only optimal, but also computationally efficient through judicious choices of the optimization trajectory