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In this paper, downlink joint user association, codebook assignment and power allocation for a Sparse Code Multiple Access (SCMA)‐based in Cloud Radio Access Network (C‐RAN) are investigated. The main aim of this paper is to accomplish a resource allocation to achieve the maximum total sum rate subject to SCMA limitation, total available power in Radio Remote Head (RRH), fronthaul constraint, users association, user power constraint, and Quality of Service requirements for each user with low complexity. To solve the recommended problem an iterative algorithm considering Successive Convex Approximation is utilized. The main problem is separated into two subproblems of joint user association and codebook assignment and power allocation. By defining a new binary variable for user association and codebook assignment and a new constraint for the user association, the joint user association and codebook assignment subproblem becomes an Integer Linear Programming. Then user association and codebook assignment subproblem solved with the help of the CVX toolbox and MOSEK solver. Furthermore, to solve the power allocation subproblem, Successive Convex Approximation with Low Complexity is applied. Then the power allocation subproblem solved by subgradient method for the Lagrange dual problem. In the simulation results, the effectiveness of the recommended optimization algorithm and resource allocation method are shown and compared to Non‐Orthogonal Multiple Access and Orthogonal Frequency Division Multiple Access.

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This work considers two‐way communication between each pair of users with highly delay‐aware applications. We formulate a joint uplink and downlink resource allocation problem in a cloud radio access network. Assuming average end‐to‐end (E2E) delay of each user pair and practical limitation such as maximum transmit power, we maximize the total throughput of all pair of users in the cloud radio access network. In this setup, we consider that each user can be connected to at most one remote radio head and a limited capacity fronthaul link between each remote radio head and baseband unit. To present the resource allocation problem in a more tractable manner, we replace the E2E delay limitation with its equivalent throughput‐based formulation. Due to inherent NP‐hard and nonconvex nature of the proposed problem, we apply successive convex approximation to reach a two‐step iterative algorithm where, in each step, a specific set of optimization variable derived while other variables are fixed. The problem of each step is transformed into the standard geometric programming via the arithmetic‐geometric mean approximation. Simulation results reveal that our proposed joint uplink‐downlink resource allocation algorithm outperforms a case that uplink and downlink resources are allocated separately in terms of total throughput and outage probability of E2E delay, ie, a chance that E2E delay does not hold.

Coherent detection in OFDM systems requires accurate channel state information (CSI) at the receiver. Channel estimation based on pilot-symbol-assisted transmissions provides a reliable way to obtain CSI. Use of pilot symbols for channel estimation, introduces overhead and it is desirable to keep the number of pilot symbols as minimum as possible. This paper introduces a new tight bound for the number of pilots in channel estimation using adaptive scheme in OFDM systems. We calculate the minimum number of necessary pilots using two approaches. The first approach for the number of pilots is obtained based on Doppler frequency shift estimation and the second approach is acquired based on channel length estimation using second order statistics of received signal. Finally we obtain the tight bound for the number of pilots using attained values

In this paper, we propose smart step closed-loop power control (SSPC) algorithm in a direct sequence-code division multiple access (DS-CDMA) receiver in the presence of frequency-selective Rayleigh fading. This receiver consists of three stages. In the first stage, with conjugate gradient (CG) adaptive beamforming algorithm, the desired users' signal in an arbitrary path is passed and the inter-path interference is canceled in other paths in each RAKE finger. Also in this stage, the multiple access interference (MAI) from other users is reduced. Thus, the matched filter (MF) can be used for the MAI reduction in each RAKE finger in the second stage. Also in the third stage, the output signals from the matched filters are combined according to the conventional maximal ratio combining (MRC) principle and then are fed into the decision circuit of the desired user. The simulation results indicate that the convergence speed of the SSPC algorithm is faster than other algorithms. Also, we observe that significant saving in total transmit power (TTP) are possible with our proposed algorithm.