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|Title:||On the minimum latency transmission scheduling in wireless networks with power control under SINR constraints||Authors:||Charalambous, Themistoklis
Deliparaschos, Kyriakos M.
|Keywords:||Wireless network;Communication links||Category:||Electrical Engineering - Electronic Engineering - Information Engineering||Field:||Engineering and Technology||Issue Date:||2015||Publisher:||John Wiley & Sons, Ltd.||Source:||Transactions on Emerging Telecommunications Technologies, 2015, Volume 26, Issue 3, Pages 367–379||Abstract:||In order to alleviate interference and contention in a wireless network, we may exploit the existence of multiple orthogonalchannels or time slots, thus achieving a substantial improvement in performance. In this paper, we study a joint transmissionscheduling and power control problem that arises in wireless networks. The goal is to assign channels (or time slots)and transmitting powers to communication links such that all communication requests are processed correctly, specifiedquality-of-service requirements are met, and the number of required time slots is minimised. First, we formulate theproblem as a mixed-integer linear programming. Then, we show that the problem considered is non-deterministicpolynomial-time hard, and subsequently, we propose non-trivial bounding techniques to solve it. Optimisation methodsare also discussed, including a column generation approach, specifically designed to find bounds for the transmissionscheduling problem. Moreover, we develop optimisation techniques in which the bounding techniques are integrated inorder to derive the optimal solution to the problem faster. We close with an extensive computational study, which showsthat despite the complexity of the problem, the proposed methodology scales to problems of non-trivial size. Our algorithmscan therefore be used for static wireless networks where propagation conditions are almost constant and a centralised agentis available (e.g. cellular networks where the base station can act as a centralised agent or wireless mesh networks), andthey can also serve as a benchmark for the performance evaluation of heuristic, approximation or distributed algorithmsthat aim to find near-optimal solutions without information about the whole network.||URI:||http://ktisis.cut.ac.cy/handle/10488/8174||ISSN:||2161-3915||DOI:||10.1002/ett.2616||Rights:||© John Wiley & Sons||Type:||Article|
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