Sharif Digital Repository

In this article, we present a cross-layer adaptive algorithm that dynamically maximizes the average utility function. A per stage utility function is defined for each link of a carrier sense multiple access-based wireless network as a weighted concave function of energy consumption, smoothed rate, and smoothed queue size. Hence, by selecting weights we can control the trade-off among them. Using dynamic programming, the utility function is maximized by dynamically adapting channel access, modulation, and coding according to the queue size and quality of the time-varying channel. We show that the optimal transmission policy has a threshold structure versus the channel state where the optimal... 

IN this paper the effect of different channel estimation approaches in OFDMA uplink system which are based on Basis Expansion Model (BEM) and widely used to consider time varying channels are discussed. It has been shown in previous works that modeling error will be reduced by applying oversampled BEM with cost of increasing sensitivity to noise. This problem will be solved by combining oversampled BEM and MMSE channel estimator with cost of increasing computational complexity. In this paper a novel channel estimation approach is represented in which by combining oversampled BEM and low rank MMSE in frequency domain, almost the same performance as the full rank MMSE has been achieved while... 

Wireless OFDM channels can be approximated by a time varying filter with sparse time domain taps. Recent achievements in sparse signal processing such as compressed sensing have facilitated the use of sparsity in estimation, which improves the performance significantly. The problem of these sparse-based methods is the need for a stable transformation matrix which is not fulfilled in the current transmission setups. To assist the analog filtering at the receiver, the transmitter leaves some of the subcarriers at both edges of the bandwidth unused which results in an ill-conditioned DFT submatrix. To overcome this difficulty we propose Adaptive Thresholding for Sparse Signal Detection (ATSSD)....