POWER CONTROL PROTOCOLS FOR WIRELESS AD HOC NETWORKS in Visual Studio .NET

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POWER CONTROL PROTOCOLS FOR WIRELESS AD HOC NETWORKS
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all, and the optimal link schedule time-shares a small number of optimal subsets of links ( L + 1, where L is the number of links) in order to achieve the required data rates. Radunovic and Le Boudec [55] studied the problem of optimal power control, scheduling, and routing in UWB wireless networks. In UWB wireless network, the link capacity is a linear function of the SINR at the receiver. For this particular physical-layer characteristic, the authors prove that the optimal power control policy is sending at the full power whenever data are sent over a link; otherwise, the link should remain silent. The reason is that the rate on a UWB link can always increase when the SINR at the receiver is increased. Even though an increase of a transmit power will increase interference at other receivers, this will always be compensated by the increase of the rate on the link itself. The optimal MAC design should be a combination of rate adaptation and mutual exclusion. The rates of senders should be adapted to the amount of noise and interference at the receiver; and when a node is receiving, it should maintain an exclusion region where any nodes in this region should remain silent during the reception. The size of this exclusion region depends only on the power constraints of the source of the transmission, and not on the length of this link or the position of other nodes. The optimal routing algorithm is minimum energy routing (MER) not only from the energy but also from throughput performance viewpoint for static networks. Another interesting result is that MAC layer is insensitivity to the choice of routes; that is, the optimal MAC protocol does not depend on the choice of routes. Bhatia and Kodialam [15] consider the joint scheduling, routing, and power control design for power-ef cient communication in wireless multihop networks. The overall problem is formulated as an optimization problem with nonlinear objective function and nonlinear constraints, and the derived solution is a performance-guaranteed polynomial time approximation algorithm for jointly solving these three problems. The authors rst consider the joint scheduling and power control problem under given ow rates and xed routes. They assume the Additive White Gaussian Noise (AWGN) channel in the physical layer, and rate-power function is R = W log2 (1 + NPW ). Thus, 0 the joint scheduling and power control problem is also the problem of joint scheduling and rate adaptation. First they get the minimum power levels and data rates required to support the ow rates. However, this does not guarantee that we will nd a link schedule to satisfy the obtained solution. Thus, a scale factor is computed to scale-up the data rates, in order to nd a schedule that support the given ow rate. Therefore, the algorithm is a near-optimal approximation algorithm that consumes more energy, and the authors prove that they can approximate the optimal solution by a factor of 3. By appropriate transformation of the original optimization problem, the original problem can be transformed into a Quadratically Constrained Programming problem [56] with only ow rates as the optimization variables. The transformed problem can be solved in polynomial time for example, using the interior point method. The authors also propose an iterative algorithm based on the Frank Wolfe method [57], which is ef cient in practice and has the nice property that it can be computed in distributed way. In each iteration, the optimal routing policy is shortest path routing.
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POWER CONTROL: THE SYSTEMATIC APPROACH
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11.4.2 Power Control: Other Approaches As mentioned in Section 11.3.1, PCDC considers the interplay between power control, MAC, and routing. The scheme can ef ciently save energy and increase the throughput at the same time. Li and Ephermides [58] propose a heuristic solution to the joint scheduling, power control, and routing algorithm for wireless ad hoc networks. They assume a TDMA-based wireless ad hoc network where each node has one transceiver. They consider the joint scheduling, routing, and power control problem as two subproblems: (a) joint scheduling and power control subproblem and (b) joint scheduling and routing subproblem. The joint scheduling and power control algorithm is similar to the one in reference 40, and the main idea is to iteratively update the power level of links while making sure that all the scheduled links satisfy their SIR requirement. The link metrics are based on queue size of links, and the link with lower link metric has higher priority in the scheduling to occupy the timeslot and update the power level as follows: Pi
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