Cross-layer optimisation of network performance over multiple-input multiple-output wireless mobile channels

2010 ◽  
Vol 4 (6) ◽  
pp. 683 ◽  
Author(s):  
M. Luccini ◽  
A. Shami ◽  
S. Primak
Keyword(s):  
Network Performance ◽  
Multiple Input Multiple Output ◽  
Cross Layer ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mobile Channels ◽  
Wireless Mobile

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.

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 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.

scholarly journals PAPR and ISI Reduction in Cognitive Radio Network based 5G Network using Massive MIMO SC - FDMA ES.

2019 ◽  
Vol 9 (1) ◽  
pp. 4697-4705
Keyword(s):  
Cognitive Radio ◽  
Massive Mimo ◽  
Network Performance ◽  
Multiple Input Multiple Output ◽  
Average Power ◽  
Network Simulator ◽  
Fifth Generation ◽  
5G Network ◽  
Multiple Input ◽  
Input Multiple Output

Extended use of spectrum increased the number of users; this was the major cause to introduce Cognitive Radio Networks (CRN) which is designed to access the available spectrum effectively. Advanced telecommunication technology that is fifth-generation (5G) is inbuilt in CRNs. Fusion Center (FC) in CRN plays an important role in decision making for allocating available spectrum. A novel FC rotation (FCR) method is applied over FC to mitigate the occurrence of interference. Massive-Multiple Input Multiple Output (MaMi) system is used to enhance network performances to accommodate the huge participation of users by means of having a large number of antennas. Existing research works in CRN based 5G network fails to decrease intersymbol interference (ISI) and Peak-to-Average Power Ratio (PAPR). A novel Massive MIMO SC – FDMA ES is proposed in this paper to mitigate high PAPR values to enhance network performance. Our proposed work in CRN is experimentally designed using Network Simulator 3 from which the performances are evaluated. The extensive simulation result shows betterment in terms of channel capacity, reduction of PAPR, bit error rate and spectral efficiency.

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