scholarly journals Cross-Layer Optimization for Heterogeneous MU-MIMO/OFDMA Networks

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2744
Author(s):  
Kyu-haeng Lee ◽  
Daehee Kim
Keyword(s):  
Network Performance ◽  
Heterogeneous Wireless Networks ◽  
Multiple Input Multiple Output ◽  
Mixed Integer ◽  
Cross Layer ◽  
Network Resources ◽  
Cross Layer Optimization ◽  
Proposed Model ◽  
Input Multiple Output ◽  
Flexible Resource

To enable the full benefits from MU-MIMO (Multiuser-Multiple Input Multiple Output) and OFDMA (Orthogonal Frequency Division Multiple Access) to be achieved, the optimal use of these two technologies for a given set of network resources has been investigated in a rich body of literature. However, most of these studies have focused either on maximizing the performance of only one of these schemes, or have considered both but only for single-hop networks, in which the effect of the interference between nodes is relatively limited, thus causing the network performance to be overestimated. In addition, the heterogeneity of the nodes has not been sufficiently considered, and in particular, the joint use of OFDMA and MU-MIMO has been assumed to be always available at all nodes. In this paper, we propose a cross-layer optimization framework that considers both OFDMA and MU-MIMO for heterogeneous wireless networks. Not only does our model assume that the nodes have different capabilities, in terms of bandwidth and the number of antennas, but it also supports practical use cases in which nodes can support either OFDMA or MU-MIMO, or both at the same time. Our optimization model carefully takes into account the interactions between the key elements of the physical layer to the network layer. In addition, we consider multi-hop networks, and capture the complicated interference relationships between nodes as well as multi-path routing via multi-user transmissions. We formulate the proposed model as a Mixed Integer Linear Programming (MILP) problem, and initially model the case in which each node can selectively use either OFDMA or MU-MIMO; we then extend this to scenarios in which they are jointly used. As a case study, we apply the proposed model to sum-rate maximization and max–min fair allocation, and verify through MATLAB numerical evaluations that it can take appropriate advantage of each technology for a given set of network resources. Based on the optimization results, we also observe that when the two technologies are jointly used, more multi-user transmissions are enabled thanks to flexible resource allocation, meaning that greater use of the link capacity is achieved.

Cross layer design with extensive virtual MIMO: FS-MUP optimization model for wireless sensor network

2020 ◽  
pp. 1-16
Author(s):  
Monali Prajapati ◽  
Dr. Jay Joshi
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Multiple Input Multiple Output ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Cross Layer Design ◽  
Virtual Mimo ◽  
Proposed Model ◽  
Multiple Input ◽  
Input Multiple Output

In the wireless sensor network (WSN), wireless communication is said to be the dominant power-consuming operation and it is a challenging one. Virtual Multiple-Input–Multiple-Output (V-MIMO) technology is considered to be the energy-saving method in the WSN. In this paper, a novel multihop virtual MIMO communication protocol is designed in the WSN via cross-layer design to enhance the energy efficiency, reliability, and end-to-end (ETE) and Quality of Service (QoS) provisioning. On the basis of the proposed protocol, the optimal set of parameters concerning the transmission and the overall consumed energy by each of the packets is found. Furthermore, the modeling of ETE latency and throughput of the protocol takes place with respect to the bit-error-rate (BER). A novel hybrid optimization algorithm referred as Flight Straight Moth Updated Particle Swarm Optimization (FS-MUP) is introduced to find the optimal BER that meets the QoS, ETE requirements of each link with lower power consumption. Finally, the performance of the proposed model is evaluated over the extant models in terms of Energy Consumption and BER as well.

scholarly journals Cross Layer Optimization and Simulation of Smart Grid Home Area Network

2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Lipi K. Chhaya ◽  
Paawan Sharma ◽  
Adesh Kumar ◽  
Govind Bhagwatikar
Keyword(s):  
Smart Grid ◽  
Network Performance ◽  
Performance Enhancement ◽  
Hierarchical Architecture ◽  
Buffer Size ◽  
Cross Layer ◽  
Area Network ◽  
Frame Aggregation ◽  
Cross Layer Optimization ◽  
Layered Approach

An electrical “Grid” is a network that carries electricity from power plants to customer premises. Smart Grid is an assimilation of electrical and communication infrastructure. Smart Grid is characterized by bidirectional flow of electricity and information. Smart Grid is a complex network with hierarchical architecture. Realization of complete Smart Grid architecture necessitates diverse set of communication standards and protocols. Communication network protocols are engineered and established on the basis of layered approach. Each layer is designed to produce an explicit functionality in association with other layers. Layered approach can be modified with cross layer approach for performance enhancement. Complex and heterogeneous architecture of Smart Grid demands a deviation from primitive approach and reworking of an innovative approach. This paper describes a joint or cross layer optimization of Smart Grid home/building area network based on IEEE 802.11 standard using RIVERBED OPNET network design and simulation tool. The network performance can be improved by selecting various parameters pertaining to different layers. Simulation results are obtained for various parameters such as WLAN throughput, delay, media access delay, and retransmission attempts. The graphical results show that various parameters have divergent effects on network performance. For example, frame aggregation decreases overall delay but the network throughput is also reduced. To prevail over this effect, frame aggregation is used in combination with RTS and fragmentation mechanisms. The results show that this combination notably improves network performance. Higher value of buffer size considerably increases throughput but the delay is also greater and thus the choice of optimum value of buffer size is inevitable for network performance optimization. Parameter optimization significantly enhances the performance of a designed network. This paper is expected to serve as a comprehensive analysis and performance enhancement of communication standard suitable for Smart Grid HAN applications.

scholarly journals SCMA-MIMO system with adaptation to the channel state

2021 ◽  
Vol 2134 (1) ◽  
pp. 012025
Author(s):  
Dmitriy Pokamestov ◽  
Yakov Kryukov ◽  
Eugeniy Rogozhnikov ◽  
Islam Kanatbekuli ◽  
Edgar Dmitriyev
Keyword(s):  
Communication System ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Access ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Network Resources ◽  
Multiple Input ◽  
The Matrix ◽  
High Spectral Efficiency ◽  
Input Multiple Output

Abstract Sparse code multiple access (SCMA) is one of the promising implementations of non-orthogonal multiple access (NOMA) methods. SCMA provides high spectral efficiency and a large number of network resources. We describe a communication system with SCMA, space-time block coding (STBC), multiple input multiple output (MIMO) technology, and orthogonal frequency division multiplexing (OFDM). The architecture of such systems, including algorithms of formation and processing of signals is considered. A method for adapting signals to the state of the spatial channel transmission based on information about the matrix of channel coefficients is proposed. The application of such adaptation allows to compensate the influence of the channel and to reduce the probability of bit errors. We consider the bit error rate (BER) performance of the communication system in different channel models and show the effectiveness of the proposed methods.

Asynchronous Media Access Control Protocols and Cross Layer Optimizations for Wireless Sensor Networks: An Energy Efficient Perspective

2020 ◽  
Vol 17 (6) ◽  
pp. 2531-2538
Author(s):  
Kalpna Guleria ◽  
Devendra Prasad ◽  
Umesh Kumar Lilhore ◽  
Sarita Simaiya
Keyword(s):  
Energy Efficient ◽  
Network Performance ◽  
Performance Metrics ◽  
Sensor Nodes ◽  
Smart Devices ◽  
Media Access Control ◽  
Cross Layer ◽  
Media Access ◽  
Cross Layer Optimization ◽  
Rapid Pace

In the recent past, the wireless technology has grown at a very rapid pace and it has brought a revolution in the field of communication. WSNs are of great importance in building the smart devices and intelligent applications such as smart homes, military surveillance applications, target tracking and structural health monitoring etc. One of the major hardware limitations is limited energy of sensor nodes which has motivated researchers to emphasize on energy efficient communication and this in turn has given a lot of stimulus for the research of energy efficient protocols for MAC and network layer. Further, the cross-layer optimizations have a major impact on network performance metrics like increased energy efficiency, enhanced reliability, reduced delay and increased security as well. In this paper, various energy efficient asynchronous MAC, MIMO-MAC layer routing protocols, analysis, cross layer optimization have been discussed.

Joint Scheduling and Precoding Based on SLNR Criteria in MU-MIMO System

2014 ◽  
Vol 668-669 ◽  
pp. 1273-1277
Author(s):  
Yang Liu ◽  
Jun Xuan Wang ◽  
Peng Wang ◽  
Ren Kai Yu
Keyword(s):  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Paper Analysis ◽  
Cross Layer ◽  
Cross Layer Design ◽  
User Scheduling ◽  
Scheduling Scheme ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Lower Complexity

The user scheduling and precoding schemes in Multi-User Multiple Input Multiple Output (MU-MIMO) system have the problem of high complexity and the performance of traditional criteria is not good. This paper analysis the advantages of Signal to Leakage plus Noise Ratio (SLNR) criteria firstly, then propose a cross-layer design of user scheduling and precoding scheme based on SLNR criteria. The design only uses SLNR criteria and includes an improved SLNR user scheduling scheme which is accomplished by iteration procedure. Numerical results verify the improved user scheduling scheme can improve the performance of sum capacity and average BER and the cross-layer design has lower complexity.

scholarly journals A Bio-Inspired QoS-Oriented Handover Model in Heterogeneous Wireless Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Daxin Tian ◽  
Jianshan Zhou ◽  
Honggang Qi ◽  
Yingrong Lu ◽  
Yunpeng Wang ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Cellular Response ◽  
Heterogeneous Wireless Networks ◽  
Resources Allocation ◽  
Network Resources ◽  
Handover Decision ◽  
Proposed Model ◽  
Wireless Environment ◽  
Wireless Environments ◽  
Attractor Selection

We propose a bio-inspired model for making handover decision in heterogeneous wireless networks. It is based on an extended attractor selection model, which is biologically inspired by the self-adaptability and robustness of cellular response to the changes in dynamic environments. The goal of the proposed model is to guarantee multiple terminals’ satisfaction by meeting the QoS requirements of those terminals’ applications, and this model also attempts to ensure the fairness of network resources allocation, in the meanwhile, to enable the QoS-oriented handover decision adaptive to dynamic wireless environments. Some numerical simulations are preformed to validate our proposed bio-inspired model in terms of adaptive attractor selection in different noisy environments. And the results of some other simulations prove that the proposed handover scheme can adapt terminals’ network selection to the varying wireless environment and benefits the QoS of multiple terminal applications simultaneously and automatically. Furthermore, the comparative analysis also shows that the bio-inspired model outperforms the utility function based handover decision scheme in terms of ensuring a better QoS satisfaction and a better fairness of network resources allocation in dynamic heterogeneous wireless networks.

scholarly journals MOS-Based Multiuser Multiapplication Cross-Layer Optimization for Mobile Multimedia Communication

2007 ◽  
Vol 2007 ◽  
pp. 1-11 ◽  
Author(s):  
Shoaib Khan ◽  
Svetoslav Duhovnikov ◽  
Eckehard Steinbach ◽  
Wolfgang Kellerer
Keyword(s):  
Perceived Quality ◽  
Cross Layer ◽  
Optimization Strategy ◽  
Network Resources ◽  
Data Link ◽  
Network Resource ◽  
Voice Communication ◽  
Cross Layer Optimization ◽  
Opinion Score ◽  
Wireless Protocol

We propose a cross-layer optimization strategy that jointly optimizes the application layer, the data-link layer, and the physical layer of a wireless protocol stack using an application-oriented objective function. The cross-layer optimization framework provides efficient allocation of wireless network resources across multiple types of applications run by different users to maximize network resource usage and user perceived quality of service. We define a novel optimization scheme based on the mean opinion score (MOS) as the unifying metric over different application classes. Our experiments, applied to scenarios where users simultaneously run three types of applications, namely voice communication, streaming video and file download, confirm that MOS-based optimization leads to significant improvement in terms of user perceived quality when compared to conventional throughput-based optimization.

Improving Sensor Network Performance with Directional Antennas: A Cross-layer Optimization

2021 ◽  
Vol 17 (4) ◽  
pp. 1-21
Author(s):  
Javier Schandy ◽  
Simon Olofsson ◽  
Nicolás Gammarano ◽  
Leonardo Steinfeld ◽  
Thiemo Voigt
Keyword(s):  
Network Performance ◽  
Low Cost ◽  
Directional Antennas ◽  
Cross Layer ◽  
Neighbor Discovery ◽  
Medium Access ◽  
Dense Networks ◽  
Cross Layer Optimization ◽  
Hidden Terminals ◽  
Network Topologies

The use of directional antennas for wireless communications brings several benefits, such as increased communication range and reduced interference. One example of directional antennas are electronically switched directional (ESD) antennas that can easily be integrated into Wireless Sensor Networks (WSNs) due to their small size and low cost. However, current literature questions the benefits of using ESD antennas in WSNs due to the increased likelihood of hidden terminals and increased power consumption. This is mainly because earlier studies have used directionality for transmissions but not for reception. In this article, we introduce novel cross-layer optimizations to fully utilize the benefits of using directional antennas. We modify the Medium Access Control (MAC) , routing, and neighbor discovery mechanisms to support directional communication. We focus on convergecast investigating a large number of different network topologies. Our experimental results, both in simulation and with real nodes, show when the traffic is dense, networks with directional antennas can significantly outperform networks with omnidirectional ones in terms of packet delivery rate, energy consumption, and energy per received packet.

Improved Model of the Selection with Soft- and Hard-Combining Decoding Strategies for Multi-User Multi-Relay Cooperative Networks

2016 ◽  
Vol 6 (4) ◽  
pp. 1766
Author(s):  
Nasaruddin Nasaruddin ◽  
Yunida Yunida ◽  
Khairul Munadi
Keyword(s):  
Network Model ◽  
Network Performance ◽  
Multiple Input Multiple Output ◽  
Original Data ◽  
Cooperative Networks ◽  
Relay Network ◽  
Relay Nodes ◽  
Data Packets ◽  
Input Multiple Output ◽  
Improved Model

In a wireless cooperative network, system reliability can be improved by introducing network coding (NC) for transmitting data packets from user to destination through relay nodes. At the destination, a decoding strategy is required to recover the original data packets. The use of NC in cooperative networks has been intensively studied in previous works in terms of the conventional model for two users and a single relay in a network. However, the network model cannot act as a virtual multiple-input multiple-output system, and a multi-user multi-relay network model could be used in a real system. Therefore, this paper proposes an improved model of two network decoding strategies, selection with soft combining (SSC) and selection with hard combining (SHC), for multi-user multi-relay cooperative networks. Users are classified based on their channel conditions, with better signal-to-noise (SNR) ratio sources being viewed as strong users, and others as weak or moderate users in the decoding strategies. To evaluate the performance of the proposed model, we first derive the bit error probability expressions for each strategy as a function of SNR and then evaluate the performance using numerical simulation for a Rayleigh fading channel. Simulation results show that SSC outperforms SHC. Furthermore, the improvement in network performance is achieved either by having a higher modulation level or using incremental relaying as the signal reception method at the destination.

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