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In this paper, we consider the power allocation problem for the downlink of the massive multiple-input multiple-output (MIMO) systems. We propose a new scheme by exploiting the water-filling algorithm in a cell with two zones. It is allocated more power to the farther users, and also users with better channel conditions receive more power in each zone. The users with better channel gain have a higher priority than others in the energy efficiency (EE) point of view. Combining the water-filling and cell division techniques in the MIMO systems leads to a reach EE maximization. We also use standard interference function (SIF) to propose a new iterative algorithm for solving the optimization problem and obtain an efficient power allocation scheme. Simulation results show that the proposed algorithm outperforms other similar algorithms from the EE point of view.

A joint scheme for the channel coding and spectrum spreading communication system is proposed in this paper. The Bit Error Rate (BER) performance of the joint proposed scheme is evaluated and compared with the case of channel coding scheme without spectrum spreading. We employ a single Low-Density Parity Check (LDPC) code for the both channel coding and direct sequence spectrum spreading. We show that the BER performance is significantly improved while the complexity does not increase too. The philosophy behind this achievement is that the spectrum spreading techniques provide the ability of channel noise protection for the communication systems by themselves.

In this paper, we investigate the energy efficient power allocation for the downlink in the massive multiple-input multiple-output (MIMO) systems under zero-forcing (ZF) receiver. The radio frequencies (RF) that have a significant effect on system performance has not been considered in most of previous researches. Increasing of random changes in RF creates a mismatch channel. We must consider the effects of the RF circuit for the performance evaluation of the massive MIMO systems. We also consider the rate of system in the presence of estimation error, similar to real world, with the quality of service (QoS) constraint and the transfer capacity of users. In the scenario of this paper, users are divided into two groups. The first group are users who have stronger channel conditions or in other words are located in the center of the cell, and the second group belongs to users who have weak channel conditions and are located at the edge of the cell. By using Karush-Kuhn-Tucker (KKT) conditions, we obtain the optimal power of users. The results of implementation and simulations are given to confirm the efficiency of the proposed algorithm.

In this paper, we investigate energy-efficient (EE) power allocation (PA) for a special downlink scenario of the massive multiple-input multiple-output (MIMO) systems. We consider a minimum power required for each user to ensure that the quality of service (QoS) for each user is satisfied. In this method, a comparison between the sum of minimum power required by users and the maximum transmission power is done to determine whether maximizing EE is possible or not. If the sum of the minimum power required by users is less than the maximum transmission power, we maximize EE. Otherwise, the number of admitted users in a cluster is maximized. In both cases, the simulation results show that the proposed algorithm has better performance than similar algorithms.

In this paper, we investigate energy-efficient power allocation for the downlink of the massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) systems. In our proposed scheme, we divide a cell into two zones. The first area is for users whose distance from the base station (BS) is less than half of the radius of cell and the second area is for users whose distance from BS is more than half of the radius of cell. Based on distance of users from BS and the number of users in each area, we dedicate an amount of power for each user. We also use standard interference function (SIF) to propose a new iterative algorithm to solve the optimization problem and obtain the optimal power allocation scheme. Simulation results show that the proposed algorithm outperforms other algorithms from the energy efficiency (EE) point of view., Comment: Accepted in GPECOM2020 2nd Global Power, Energy and Communication Conference

A comparison between the joint and the successive decoding schemes for a two-link case binary Chief Executive Officer (CEO) problem is presented. We utilize the logarithmic loss as the criterion for measuring and comparing the total distortion of the decoding techniques. The binary symmetric channel (BSC) is considered as the test-channel model, which provides a theoretical rate-distortion bound. Simulation results show that the joint decoding scheme provides smaller compression rate and distortion values compared to the successive decoding scheme. On the other hand the successive decoding method has lower complexity; therefore, it is efficient for the cases with higher number of links., Comment: 5 pages, accepted in ICEE 2020

The $L$-link binary Chief Executive Officer (CEO) problem under logarithmic loss is investigated in this paper. A quantization splitting technique is applied to convert the problem under consideration to a $(2L-1)$-step successive Wyner-Ziv (WZ) problem, for which a practical coding scheme is proposed. In the proposed scheme, low-density generator-matrix (LDGM) codes are used for binary quantization while low-density parity-check (LDPC) codes are used for syndrome generation; the decoder performs successive decoding based on the received syndromes and produces a soft reconstruction of the remote source. The simulation results indicate that the rate-distortion performance of the proposed scheme can approach the theoretical inner bound based on binary-symmetric test-channel models.

In this paper, we propose an efficient coding scheme for the two-link binary Chief Executive Officer (CEO) problem under logarithmic loss criterion. The exact rate-distortion bound for a two-link binary CEO problem under the logarithmic loss has been obtained by Courtade and Weissman. We propose an encoding scheme based on compound LDGM-LDPC codes to achieve the theoretical bounds. In the proposed encoding, a binary quantizer using LDGM codes and a syndrome-coding employing LDPC codes are applied. An iterative joint decoding is also designed as a fusion center. The proposed CEO decoder is based on the sum-product algorithm and a soft estimator., Comment: 5 pages. arXiv admin note: substantial text overlap with arXiv:1801.00435

In this paper, we propose an efficient coding scheme for the binary Chief Executive Officer (CEO) problem under logarithmic loss criterion. Courtade and Weissman obtained the exact rate-distortion bound for a two-link binary CEO problem under this criterion. We find the optimal test-channel model and its parameters for the encoder of each link by using the given bound. Furthermore, an efficient encoding scheme based on compound LDGM-LDPC codes is presented to achieve the theoretical rates. In the proposed encoding scheme, a binary quantizer using LDGM codes and a syndrome-decoding employing LDPC codes are applied. An iterative decoding is also presented as a fusion center to reconstruct the observation bits. The proposed decoder consists of a sum-product algorithm with a side information from other decoder and a soft estimator. The output of the CEO decoder is the probability of source bits conditional to the received sequences of both links. This method outperforms the majority-based estimation of the source bits utilized in the prior studies of the binary CEO problem. Our numerical examples verify a close performance of the proposed coding scheme to the theoretical bound in several cases., Comment: 28 pages

In this paper, a practical coding scheme is designed for the binary Wyner-Ziv (WZ) problem by using nested low-density generator-matrix (LDGM) and low-density parity-check (LDPC) codes. This scheme contains two steps in the encoding procedure. The first step involves applying the binary quantization by employing LDGM codes and the second one is using the syndrome-coding technique by utilizing LDPC codes. The decoding algorithm of the proposed scheme is based on the Sum-Product (SP) algorithm with the help of a side information available at the decoder side. It is theoretically shown that the compound structure has the capability of achieving the WZ bound. The proposed method approaches this bound by utilizing the iterative message-passing algorithms in both encoding and decoding, although theoretical results show that it is asymptotically achievable.