Search

This paper discusses the operation of a massive multiple‐input multiple‐output (MIMO) system from a different perspective. The system is performed in the presence of an eavesdropper who is trying to disrupt the message being transmitted between the base station (BS) and the users. An attempt has been made to maximize the secure energy efficiency (EE) of the system by allocating appropriate power to each user. The channel state information (CSI) between users and the BS is considered imperfect and the employed precoding scheme is the zero forcing (ZF). The CSI related to the eavesdropper is considered to be perfect and its precoding is assumed to be the maximum ratio transmission (MRT). The problem of optimization that is for maximizing the EE has two constraints including the maximum transmission power and the minimum user data rate. To improve the performance of system, the cell division technique is applied, which results in approaching the performance of system to the without eavesdropper scenario. Five various scenarios have been investigated in this research, and it is proved that the proposed method improves the system performance in all cases. The numerical and simulation results obtained from implementation of the proposed algorithm confirm the claim. [ABSTRACT FROM AUTHOR]

The demand for less complex and more accurate architectures has always been a priority since the broad usage of computer vision in everyday life, like auto‐drive cars, portable applications, augmented reality systems, medical image analysis etc. There are a lot of methods that have been developed to improve the accuracy and complexity of object detection, like the generations of R‐CNNs and YOLOs. However, these methods are not the most efficient architectures, and there is always room to improve. In this study, the 5th version of YOLO is employed and the improved architecture, Inception‐YOLO, is presented. The model significantly outperforms the SOTA YOLO family. Specifically, the improvements can be summarised as follows: impressive improvement of floating point operations (FLOPs) and number of parameters, as well as improvement in accuracy compared to the models with fewer FLOPs. All our presented approaches, like the optimized inception module, proposed structures for CSP and SPPF, and the improved loss function used in this research, work together to incrementally improve detection results, accuracy, demanded memory, and FLOPs simultaneously. For a glimpse of performance, the Inception‐YOLO‐S model hits 38.7% AP with 5.9M parameters and 11.5 BFLOPs and outperforms YOLOv5‐S with 37.4% AP, 7.2M parameters, and 16.5 BFLOPs. [ABSTRACT FROM AUTHOR]

In this paper, we present a practical encoding and decoding scheme for the binary Wyner-Ziv problem based on graph-based codes. Our proposed scheme uses low-density generator-matrix (LDGM) codes in lossy source coding part and low-density parity-check (LDPC) codes in syndrome generation and decoding part. Actually, we apply Bias-Propagation algorithm for lossy source coding or binary quantization and Sum-Product algorithm for syndrome-based channel decoding. Using appropriate degree distributions for LDGM codes and optimized degree distributions for LDPC codes, we will be able to achieve close rate-distortion performance to the theoretical Wyner-Ziv bound. Also, we extend our proposed scheme for presenting a practical coding scheme for the binary Chief Executive Officer (CEO) problem. In our scheme, encodig is based on binary-quantization and Slepian-Wolf coding using source-splitting technique. It is shown that, source-splitting technique is an efficient strategy for achieving non-corner points in Slepian-Wolf rate region. We show that, this technique along with iterative message-passing algorithms can be efficient for having close rate-distortion performance to the Berger-Tung inner bound of binary CEO problem for non-corner points too. [ABSTRACT FROM AUTHOR]

Summary: Multiple‐input multiple‐output (MIMO) systems perform well from the energy efficiency (EE) and the spectral efficiency (SE) points of view in fifth generation (5G) communication systems. This paper considers the operation of a MIMO system with a relay. The optimization problem relates to the EE maximization. This problem has two types of limitations, which provide a maximum transmission power and a minimum data rate for users. The encountered objective function is in a fractional form and thus it is a non‐convex function. Besides, the problem is constrained. We utilize a lower bound analysis for the data rates, some properties of the linear programming, and the maximum ratio transmission (MRT) precoding scheme to obtain a convex objective function. Using the Lagrange dual function, we obliterate the constraints of the problem and then it is easy to solve. To improve system performance, users are divided into two groups based on their channel gains, and the maximum transmission power is reasonably divided between them. Two iterative algorithms are proposed to solve the optimization problem numerically, and finally we investigate performance of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: There are many challenges in fifth generation (5G) telecommunication systems, due to the increasing demands and applications. The most important of which are need to have higher energy efficiency (EE) and spectral efficiency (SE). They are critical in the practical multiple‐input multiple‐output (MIMO) telecommunication systems. Non‐orthogonal multiple access (NOMA) methods and millimeter‐waves can be used in conjunction with MIMO systems to improve their EE and SE performance. In this paper, we investigate the application of NOMA and mm‐Wave transmission in the downlink of MIMO systems. Then, we formulate the optimization problem for users in MIMO‐NOMA systems to maximize the EE that is subject to minimum data rate to satisfy required quality of service (QoS) and maximum transmission power. To achieve the optimal power allocation for users, we reach a problem for the EE maximization that is non‐convex and solution of the optimization problem is not trivial. We exploit a lower bound of the data rate and the Lagrange dual function to convert it to a convex and unconstrained problem, which is easy to solve. In the next step, we derive a relation for determining the optimal power allocation of users. In addition, a numerical algorithm is presented that can be used to solve the problem. According to the simulation results of the proposed algorithm, our method performs better and provides higher EE than both orthogonal multiple access and equal power allocation schemes. [ABSTRACT FROM AUTHOR]

In this paper, the performance of a system in terms of the energy efficiency (EE) is studied. To check the EE performance, an appropriate power is allocated to each user. The system in question in this paper is a multiple-input multiple-output (MIMO) system with non-orthogonal multiple access (NOMA) method. Precoding in this system is considered to be the zero forcing (ZF). It is also assumed that the channel state information (CSI) mode is perfect. First, all the parameters that affect the channel, such as path loss and beam forming are investigated, and then the channel matrix is obtained. To improve system performance, better conditions are provided for users with poor channel conditions. These conditions are created by allocating more appropriate power to these users, or in other words, the total transmission power is divided according to the distance of users from the base station (BS) and the channel conditions of each user. The problem of maximizing the EE is formulated with two constraints of the minimum user rate and the maximum transmission power. This is a non-convex problem that becomes a convex problem using optimization properties, and because the problem is constrained it becomes an unconstrained problem using the Lagrange dual function. Numerical and simulation results are presented to prove the mathematical relationships which show that the performance of the proposed scheme is improved compared to the existing methods. The simulation results are related to two different algorithms with a same objective function. Furthermore, to comparison with performance of other methods, output of these two algorithms are also compared with each other. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we study energy‐efficient power allocation (PA) to secure the confidential information of massive multiple‐input multiple‐output (MIMO) systems in the presence of an eavesdropper. First a training scheme is presented in the uplink using the MMSE method. Based on the estimated channel state information (CSI), the base station (BS) encrypts the confidential information. Next, the ergodic secret rate is obtained at the downlink. In this paper, in order to maximize the ergodic secrecy rate, the allocation of common power in the uplink and downlink is proposed by considering the constraints such as the transmit power constraint in the uplink, the transmit power constraint in the downlink, and the minimum ergodic secret rate constraint. The objective function in the proposed scenario is a nonconvex problem, which first becomes a convex problem and then, by using the Lagrange dual function method, the problem becomes an unconstraint problem. We also divide the cell into two areas using the cell division method. A practical energy‐efficient PA algorithm is presented which deals with the adverse effect of the eavesdropper. Simulations are carried out to demonstrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 optimal parameters of the binary symmetric test-channel model for the encoder of each link by using the given bound. Furthermore, an efficient coding scheme based on compound low-density generator matrix (LDGM)–low-density parity-check (LDPC) codes is presented to achieve the theoretical rates. In the proposed encoding scheme, a binary quantizer using LDGM codes and a syndrome generator using LDPC codes are applied. The proposed decoder employs a sum-product algorithm and a soft estimator to produce an approximate a posteriori distribution of the source bits given the data received through both links. Our numerical examples verify a close performance of the proposed coding scheme to the theoretical bound in several cases. [ABSTRACT FROM AUTHOR]