Sharif Digital Repository

We consider a wireless distributed computing system, in which multiple mobile users, connected wirelessly through an access point, collaborate to perform a computation task. In particular, users communicate with each other via the access point to exchange their locally computed intermediate computation results, which is known as data shuffling. We propose a scalable framework for this system, in which the required communication bandwidth for data shuffling does not increase with the number of users in the network. The key idea is to utilize a particular repetitive pattern of placing the data set (thus a particular repetitive pattern of intermediate computations), in order to provide the... 

This paper considers a resource allocation problem in device-to-device (D2D) communications sharing the same frequency spectrum. In particular, the cellular users (CUs) utilize non-orthogonal multiple access (NOMA) while D2D users (DUs) adopt the orthogonal frequency division multiple access (OFDMA). A multi-objective optimization problem (MOOP) is formulated, which jointly maximizes the sum rate of DUs and CUs in uplink communications while taking into account the maximum transmit power budget and minimum data rate requirement for DUs and CUs. This MOOP is handled by the weighted Tchebycheff method, which converts it into a single-objective optimization (SOOP). Then, the monotonic... 

In the realization of adaptive beamforming algorithms, the least-mean-squares (LMS) algorithm had been the most popular scheme used for Smart Antenna systems. This Paper proposes an alternate scheme in the form of the Normalized LMS (NLMS) algorithm with active tap detection for WCDMA systems. By taking advantage of spatial filtering, the proposed scheme promises to reduce the bandwidth required for transmitting data by improving convergence rate. The performance of the Frequency Domain NLMS algorithm in the presence of multipath effects and multiple users is analyzed using simulations. This analysis is compared to that of LMS algorithm and suggests improvement in the convergence rate and... 

In this paper, we study a resource allocation problem in orthogonal frequency division multiple access (OFDMA)-based Device-to-Device (D2D) communications. To this end, we propose a multi-objective optimization problem (MOOP) framework, which jointly maximizes the sum rate of D2D users (DUs) and cellular users (CUs) in uplink communications and minimizes the total transmit power. The proposed problem formulation takes into account the minimum data-rates and the maximum transmitted power budget for both DUs and CUs. We transform this MOOP into a single-objective optimization problem (SOOP) using the weighted sum method and then propose an approach to solve this SOOP via a monotonic approach...