On the Optimal Precoder Design for Energy-Efficient and Secure MIMO Systems

2017 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Tung T. Vu ◽  
Ha Hoang Kha
Keyword(s):  
Energy Efficiency ◽  
Mimo Systems ◽  
Search Algorithm ◽  
Multiple Input Multiple Output ◽  
Research Work ◽  
Computational Cost ◽  
Optimal Solution ◽  
Secrecy Rate ◽  
Highly Nonlinear ◽  
Precoder Design

In this research work, we investigate precoder designs to maximize the energy efficiency (EE) of secure multiple-input multiple-output (MIMO) systems in the presence of an eavesdropper. In general, the secure energy efficiency maximization (SEEM) problem is highly nonlinear and nonconvex and hard to be solved directly. To overcome this difficulty, we employ a branch-and-reduce-and-bound (BRB) approach to obtain the globally optimal solution. Since it is observed that the BRB algorithm suffers from highly computational cost, its globally optimal solution is importantly served as a benchmark for the performance evaluation of the suboptimal algorithms. Additionally, we also develop a low-complexity approach using the well-known zero-forcing (ZF) technique to cancel the wiretapped signal, making the design problem more amenable. Using the ZF based method, we transform the SEEM problem to a concave-convex fractional one which can be solved by applying the combination of the Dinkelbach and bisection search algorithm. Simulation results show that the ZF-based method can converge fast and obtain a sub-optimal EE performance which is closed to the optimal EE performance of the BRB method. The ZF based scheme also shows its advantages in terms of the energy efficiency in comparison with the conventional secrecy rate maximization precoder design.

An Efficient Distributed Single-hop Relay Supporting (EDSRS) MAC Protocol for Wireless Sensor Networks

2019 ◽  
Vol 9 (2) ◽  
pp. 153-164
Author(s):  
Arvind Kakria ◽  
Trilok Chand Aseri
Keyword(s):  
Energy Efficiency ◽  
Cooperative Communication ◽  
Mimo Systems ◽  
Mac Protocol ◽  
Multiple Input Multiple Output ◽  
Relay Node ◽  
Base Stations ◽  
Destination Node ◽  
Distributed Coordination ◽  
Hardware Complexity

Background & Objective: Wireless communication has immensely grown during the past few decades due to significant demand for mobile access. Although cost-effective as compared to their wired counterpart, maintaining good quality-of-service (QoS) in these networks has always remained a challenge. Multiple-input Multiple-output (MIMO) systems, which consists of multiple transmitter and receiver antennas, have been widely acknowledged for their QoS and transmit diversity. Though suited for cellular base stations, MIMO systems are not suited for small-sized wireless nodes due to their hardware complexity, cost, and increased power requirements. Cooperative communication that allows relays, i.e. mobile or fixed nodes in a communication network, to share their resources and forward other node’s data to the destination node has substituted the MIMO systems nowadays. To harness the full benefit of cooperative communication, appropriate relay node selection is very important. This paper presents an efficient single-hop distributed relay supporting medium access control (MAC) protocol (EDSRS) that works in the single-hop environment and improves the energy efficiency and the life of relay nodes without compensating the throughput of the network. Methods: The protocol has been simulated using NS2 simulator. The proposed protocol is compared with energy efficient cooperative MAC protocol (EECOMAC) and legacy distributed coordination function (DCF) on the basis of throughput, energy efficiency, transmission delay and an end to end delay with various payload sizes. Result and Conclusion: The result of the comparison indicates that the proposed protocol (EDSRS) outperforms the other two protocols.

scholarly journals Energy Efficiency Design for Secure MISO Cognitive Radio Network Based on a Nonlinear EH Model

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Lei Ni ◽  
Xinyu Da ◽  
Hang Hu ◽  
Miao Zhang
Keyword(s):  
Energy Efficiency ◽  
Cognitive Radio ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Primary User ◽  
Open Architecture ◽  
Maximization Problem ◽  
Transmit Beamforming ◽  
Secrecy Rate ◽  
Single Output

In this work, we investigate the secrecy energy efficiency (SEE) optimization problem for a multiple-input single-output (MISO) cognitive radio (CR) network based on a practical nonlinear energy-harvesting (EH) model. In particular, the energy receiver (ER) is assumed to be a potential eavesdropper due to the open architecture of a CR network with simultaneous wireless information and power transfer (SWIPT), such that the confidential message is prone to be intercepted in wireless communications. The aim of this work is to provide a secure transmit beamforming design while satisfying the minimum secrecy rate target, the minimum EH requirement, and the maximum interference leakage power to primary user (PU). In addition, we consider that all the channel state information (CSI) is perfectly known at the secondary transmitter (ST). We formulate this beamforming design as a SEE maximization problem; however, the original optimization problem is not convex due to the nonlinear fractional objective function. To solve it, a novel iterative algorithm is proposed to obtain the globally optimal solution of the primal problem by using the nonlinear fractional programming and sequential programming. Finally, numerical simulation results are presented to validate the performance of the proposed scheme.

scholarly journals Massive MIMO-NOMA Networks with Imperfect SIC: Design and Fairness Enhancement

2020 ◽  
Author(s):  
Arthur Sousa de Sena ◽  
Pedro Nardelli
Keyword(s):  
Outage Probability ◽  
Power Allocation ◽  
Interference Cancellation ◽  
Massive Mimo ◽  
Multiple Access ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Optimal Solution ◽  
Input Multiple Output ◽  
The Impact

This paper addresses multi-user multi-cluster massive multiple-input-multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA). Assuming the downlink mode, and taking into consideration the impact of imperfect successive interference cancellation (SIC), an in-depth analytical analysis is carried out, in which closed-form expressions for the outage probability and ergodic rates are derived. Subsequently, the power allocation coefficients of users within each sub-group are optimized to maximize fairness. The considered power optimization is simplified to a convex problem, which makes it possible to obtain the optimal solution via Karush-Kuhn-Tucker (KKT) conditions. Based on the achieved solution, we propose an iterative algorithm to provide fairness also among different sub-groups. Simulation results alongside with insightful discussions are provided to investigate the impact of imperfect SIC and demonstrate the fairness superiority of the proposed dynamic power allocation policies. For example, our results show that if the residual error propagation levels are high, the employment of orthogonal multiple access (OMA) is always preferable than NOMA. It is also shown that the proposed power allocation outperforms conventional massive MIMO-NOMA setups operating with fixed power allocation strategies in terms of outage probability.

scholarly journals Design Issues and Challenges in Indoor MIMO Antenna Systems

2020 ◽  
Vol 8 (6) ◽  
pp. 3842-3846
Keyword(s):  
High Speed ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Research Work ◽  
Antenna System ◽  
Design Parameters ◽  
Future Research ◽  
Design Issues ◽  
Mimo Antenna

The promising solution for next generation wireless communication system is multiple input multiple output (MIMO) system. It can transmit and receive data from different channels simultaneously without any need of additional frequency band. In this paper the design issues and challenges in MIMO antenna system for different applications have been reviewed. The major applications of MIMO systems include Wi-Fi, High Speed Packet Access, LTE, WiMAX (4G), and also MIMO has been used in power line communication. Implementation of MIMO antenna system is dependent on important parameters such as: Peak gain, Average Gain, Mutual Coupling, Envelop Correlation Coefficient (ECC), Total Active Reflection Coefficient (TARC), Signal polarization and Miniaturization of antenna system. Hence an optimal MIMO antenna design to suit for communication applications in an indoor environment is a challenging task. This paper proposes comparative study for the different MIMO antenna parameters. The different modeling techniques for MIMO antenna system are surveyed and areas for future research work in line with tradeoffs between different design parameters are suggested.

scholarly journals Energy Efficiency-Oriented Resource Allocation for Massive MIMO Systems with Separated Channel Estimation and Feedback

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 582
Author(s):  
Feng Hu ◽  
Kaiyue Wang ◽  
Shufeng Li ◽  
Libiao Jin
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Optimal Solution ◽  
Optimization Procedure ◽  
Spatial Separation ◽  
Low Complexity ◽  
Maximization Problem

This paper proposes a dynamic resource allocation scheme to maximize the energy efficiency (EE) for Massive MIMO Systems. The imperfect channel estimation (CE) and feedback are explicitly considered in the EE maximization problem, which aim to optimize the power allocation, the antenna subset selection for transmission, and the pilot assignment. Assuming CE error to be bounded for the complex-constrained Cramer–Rao Bound (CRB), theoretical results show that the lower bound is directly proportional to its number of unconstrained parameters. Utilizing this perspective, a separated and bi-directional estimation is developed to achieve both low CRB and low complexity by exploiting channel and noise spatial separation. Exploiting global optimization procedure, the optimal resource allocation can be transformed into a standard convex optimization problem. This allows us to derive an efficient iterative algorithm for obtaining the optimal solution. Numerical results are provided to demonstrate that the outperformance of the proposed algorithms are superior to existing schemes.

scholarly journals Energy Efficiency Optimization for Massive MIMO Non-Orthogonal Unicast and Multicast Transmission with Statistical CSI

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 857 ◽  
Author(s):  
Wang ◽  
Huang ◽  
You ◽  
Xiong ◽  
Li ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Maximization Problem ◽  
Multicast Transmission ◽  
Deterministic Equivalent ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Vector Valued

We study the energy efficiency (EE) optimization problem in non-orthogonal unicast and multicast transmission for massive multiple-input multiple-output (MIMO) systems with statistical channel state information of all receivers available at the transmitter. Firstly, we formulate the EE maximization problem. We reduce the number of variables to be solved and simplify this large-dimensional-matrix-valued problem into a real-vector-valued problem. Next, we lower the computational complexity significantly by replacing the objective with its deterministic equivalent to avoid the high-complex expectation operation. With guaranteed convergence, we propose an iterative algorithm on beam domain power allocation using the minorize maximize algorithm and Dinkelbach’s transform and derive the locally optimal power allocation strategy to achieve the optimal EE. Finally, we illustrate the significant EE performance gain of our EE maximization algorithm compared with the conventional approach through conducting numerical simulations.

scholarly journals Overview on Multipattern and Multipolarization Antennas for Aerospace and Terrestrial Applications

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Aixin Chen ◽  
Weiwei Jiang ◽  
Zhizhang Chen ◽  
Jiaheng Wang
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Research Work ◽  
Reconfigurable Antennas ◽  
Noisy Environment ◽  
Left Hand ◽  
Telecommunication Systems ◽  
Multiple Input ◽  
Input Multiple Output ◽  
System Requirements

In recent years, reconfigurable antennas, with the ability to radiate wave in more than one pattern and polarization, play a great role in modern telecommunication systems. Compared with conventional antennas, multipattern and multipolarization antennas have more advantages and better prospects. They can be used to improve system gain and security, satisfy system requirements, avoid noisy environment, and adapt to the environment flexibly. This paper discusses different patterns and polarizations of reconfigurable antennas according to current research work in this area. In the opinion of this paper, the radiation pattern states of antennas include beam direction, shape, and gain. The polarization states of antennas include horizontal/vertical linear, ±slant 45° linear, left-hand or right-hand circular polarized. Different multipattern and multipolarization antennas with various structures and working mechanisms are compared and discussed. Multipattern and multipolarization antennas have been well applied for aerospace and terrestrial applications, such as dynamic scenarios, adaptive beam scanning, and multiple-input-multiple-output (MIMO) systems.

Analysis of Distributed MIMO Systems in a Multi-Cell Environment

2014 ◽  
Vol 696 ◽  
pp. 183-190
Author(s):  
Yue Heng Li ◽  
Ming Hao Fu ◽  
Li Wang ◽  
Mei Yan Ju ◽  
Ping Huang
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Research Work ◽  
Network Scheduling ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Communication Scheme ◽  
Inter Cell Interference ◽  
Output Sinr ◽  
Probability Density Function Pdf

This paper focuses its research work on the capacity and outage performances of a distributed multiple-input multiple-output (DMIMO) system in a multi-cell environment. For this purpose, the multi-cell DMIMO structure is modeled first, and based on this model, the so-called blanket communication and selective communication schemes are compared, and the formula of the output signal to interference plus noise ratio (SINR) of the above two schemes are given to illustrate the way of an inter-cell interference affecting the system performance. Then the expressions of the average capacity and outage probability are derived by using the probability density function (PDF) of the output SINR in the preferred selective communication scheme with some necessary approximations. Finally, the computer simulations are provided to explore the possible rule of upper layer network scheduling in overcoming the inter-cell interferences and in optimizing the capacity and outage performances in the DMIMO systems.

scholarly journals Joint Transmit and Receive Antenna Selection in MIMO Systems Based on Swarm Intelligence Algorithm

2021 ◽  
Author(s):  
Zhang Yiwen ◽  
Su Sunqing ◽  
Liao Wenliang ◽  
Lei Guowei ◽  
Yang Guangsong
Keyword(s):  
Mimo Systems ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Optimal Solution ◽  
System Capacity ◽  
Particle Swarm Algorithm ◽  
Input Multiple Output ◽  
Swarm Algorithm ◽  
Speed Accuracy ◽  
Receive Antenna

Abstract In multiple-input-multiple-output (MIMO) systems, the selection of receive and transmit antennas is not just effective in increasing system capacity, but also in reducing RF link costs and system complexity. The exhaustive algorithm, i.e. the joint transmit and receive antenna selection (JTRAS) with the best accuracy, can search all the subsets of both transmit and receive antennas in order to find the optimal solution. However, with the increase of the number of antennas, the computational complexity is too large and its applicability is limited. In this paper, the antennas are coded by fractional coding with the maximization of channel capacity as the basic criterion, and three intelligent algorithms, namely genetic algorithm, cat swarm algorithm and particle swarm algorithm, are applied for antenna selection. The simulation results demonstrate that all three algorithms can efficiently accomplish the antenna selection. In the end, we compare them in terms of speed, accuracy and complexity of the search in MIMO systems.

Hybrid multibeam forming and multiuser detection technique for MU-MIMO system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
D. Lalitha Kumari ◽  
M.N. Giri Prasad
Keyword(s):  
Energy Efficiency ◽  
Error Rate ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Experimental Results ◽  
Rate Performance ◽  
Hardware Complexity ◽  
Content Type ◽  
Simulation Results

PurposeIn recent years, multiuser-multiple-input multiple-output (MU-MIMO)-based wireless communication system has emerged as a prominent 5G technique that has several advantages over conventional MIMO systems such as high data rate and channel capacity. In this paper, the authors introduce a novel low-complexity radix factorization-based fast Fourier transform (FFT) as a multibeamformer and maximal likelihood-MU detection (ML-MUD) techniques as an optimal signal subdetector which results with considerable complexity reduction with intolerable error rate performance.Design/methodology/approachThe proposed radix-factorized FFT-multibeamforming (RF-FFT-MBF) architectures have the potential to reduce both hardware complexity and energy consumptions as compared to its state-of-the-art methods while meeting the throughput requirements of emerging 5G devices. Here through simulation results, the efficiency of the scaled ML subdetector system is compared with the conventional ML detectors.FindingsHere through simulation results, the efficiency of the scaled ML subdetector system is compared with the conventional ML detectors. Through experimental results, it is well proved that the proposed detector offers significant hardware and energy efficiency with the least possible error rate performance overhead.Originality/valueHere through simulation results, the efficiency of the scaled ML subdetector system is compared with the conventional ML detectors. Through experimental results, it is well proved that the proposed detector offers significant hardware and energy efficiency with the least possible error rate performance overhead.

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