scholarly journals Design of an Energy Efficient Future Base Station with Large-Scale Antenna System

Energies ◽  
2016 ◽  
Vol 9 (12) ◽  
pp. 1083 ◽  
Author(s):  
Byung Lee ◽  
Youngok Kim
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Antenna System ◽  
Base Station

scholarly journals ISSOR Signal Detection for Energy Efficient and Low Complexity Large Scale MIMO System

2019 ◽  
Vol 9 (1S5) ◽  
pp. 327-334
Keyword(s):  
Signal Detection ◽  
Energy Efficient ◽  
Communication Systems ◽  
Large Scale ◽  
Mimo System ◽  
Low Complexity ◽  
High Energy ◽  
Base Station ◽  
User Equipment ◽  
Multiple User

Scalable version of multiuser MIMO called Large-scale MIMO is a one of the powerful technology in future wireless communication systems in which huge amount of BS (base station) antennas utilized to process multiple user equipment. Energy consumed is high with more antennas and also it leads to increase the signal detection complexity and overall circuit power consumption. Designing energy efficient and low complexity MIMO system is considered as a challenging issue. This paper presents the ISSOR signal detection for energy efficient and low complexity large scale MIMO system. VA-GSM (Variable Antenna Generalized spatial modulation) is used in which the number of active antenna transmissions are varied for every transmission in the large scale MIMO. In transmitter side, Eigen value based approach is used for antenna selection. Then, improved symmetric successive over relaxation (ISSOR) approach is proposed for low complexity signal detection in receiver side. The number of user equipment, transmit power, as well as the amount of antennas at the base station, are considered as the optimal system parameters which are chosen for enhancing the efficiency of utilized energy in the system. The proposed scheme implemented in MATLAB software. The proposed scheme attained the high energy efficiency compared to other approaches. Moreover, the BER is utilized to estimate the performance of an offered algorithm and also compared to the previously determined algorithm of existing literatures.

scholarly journals REGION BASED CLUSTERING FOR DATA COLLECTION IN WSN

2017 ◽  
Vol 16 (5) ◽  
pp. 6913-6919
Author(s):  
Ramandeep Kaur ◽  
Dinesh Kumar
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Smart Cities ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Cluster Head Selection ◽  
Clustering Methods ◽  
Mobile Nodes ◽  
Improved Performance

The lower cost and easier installation of the WSNs than the wired counterpart pushes industry and academia to pay more attention to this promising technology. Large scale networks of small energy-constrained sensor nodes require techniques and protocols which are scalable, robust, and energy-efficient. The most efficient approach provided by clustering the nodes is hierarchy. The one node will send the data to another node and the another node will send to its neightbouring node. In smart cities, wireless sensor networks (WSNs) act as a type of core infrastructure that collects data from the city to implement smart services. Our thesis work included the region based clustering, cluster head selection and energy efficient communication using static base station and movable mobile nodes. Since it was earlier proposed that clustering improves the network lifetime. We modified the region based clustering by dividing the network area into n regions with cluster head chosen for each region and proposed a new method for cluster head selection having less computational complexity. It was also found that the modified approach has improved performance to that of the other clustering approaches. We have used the mobile nodes for each section with controlled trajectory path as a reference to compare the performance of each of the clustering methods.

scholarly journals Limited Feedback Precoding for Massive MIMO

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Xin Su ◽  
Jie Zeng ◽  
Jingyu Li ◽  
Liping Rong ◽  
Lili Liu ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Large Scale ◽  
Multiple Input Multiple Output ◽  
Limited Feedback ◽  
Antenna System ◽  
Base Station ◽  
Array Antenna ◽  
Codebook Design ◽  
Input Multiple Output ◽  
Scenarios Simulation

The large-scale array antenna system with numerous low-power antennas deployed at the base station, also known as massive multiple-input multiple-output (MIMO), can provide a plethora of advantages over the classical array antenna system. Precoding is important to exploit massive MIMO performance, and codebook design is crucial due to the limited feedback channel. In this paper, we propose a new avenue of codebook design based on a Kronecker-type approximation of the array correlation structure for the uniform rectangular antenna array, which is preferable for the antenna deployment of massive MIMO. Although the feedback overhead is quite limited, the codebook design can provide an effective solution to support multiple users in different scenarios. Simulation results demonstrate that our proposed codebook outperforms the previously known codebooks remarkably.

scholarly journals Energy efficient optimisation for large-scale multiple-antenna system with WPT

2018 ◽  
Vol 12 (5) ◽  
pp. 552-558 ◽  
Author(s):  
Zheng Chang ◽  
Shan Zhang ◽  
Zhongyu Wang ◽  
Xijuan Guo ◽  
Zhu Han ◽  
...  
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Antenna System ◽  
Multiple Antenna ◽  
Multiple Antenna System

scholarly journals Achievable Capacity with Spatial Channel Correlation in Massive MIMO Multi-Cell Systems

2020 ◽  
Vol 9 (4) ◽  
pp. 15-20
Keyword(s):  
Large Scale ◽  
High Capacity ◽  
Antenna System ◽  
Base Station ◽  
Spatial Multiplexing ◽  
Channel Correlation ◽  
Mimo Antenna ◽  
Linearly Independent ◽  
Base Station Antennas ◽  
The Impact

Massive Multi-Input and Multi-Output (MIMO) antenna system provides unlimited capacity by the spatial multiplexing and array gain. Since the data rate has been limited by the coherence interference due to pilot contamination (PC). In this paper, we propose transmit combine and precoding schemes to achieve asymptotic capacity in multi-cell scenario, when the number of base station antennas tends to infinity. The impact of spatial channel correlation on channel capacity is explored by considering the co-variance matrices of the user –terminals (UT)s .To do this, we presented linear processing schemes such as MMSE,MRC, and ZF.Where MMSE achieves high capacity in the presence of large-scale fading and PC. Since the diagonals of the channel covariance matrices were designed with non- zero Eigen values and linearly independent. The results outperform and obtain asymptotic limit, when the co-variance of UTs are linearly independent. The results were simulated by using MATLAB 2018b.

scholarly journals Distributed Intra and Inter Cluster Chaining Framework for Energy-Efficient, Delay Bounded and Scalable Data Gathering Applications in Large Scale Sensor Network

2019 ◽  
Vol 9 (2) ◽  
pp. 2068-2075
Keyword(s):  
Sensor Network ◽  
Energy Efficient ◽  
Large Scale ◽  
Data Gathering ◽  
Base Station ◽  
Wireless Sensor ◽  
Data Delivery ◽  
Delivery Delay ◽  
Efficient Data ◽  
Bounded Data

This paper proposes a scalable, energy-efficient and scalable, energy efficient, delay bounded intra and inter cluster routing framework viz. GIICCF (Generalized Intra and Inter cluster chaining framework) for efficient data gathering in large scale wireless sensor networks. This approach extricates the benefits of both pure chain-based as well as pure cluster-based data gathering schemes in large scale Wireless Sensor Network (WSNs) without undermining with the drawbacks. GIICCF defines a localized energy-efficient chaining scheme among the member nodes within the cluster with bounded data delivery delay to the respective cluster-heads (CH) as well as enables the CH to deliver data to the Base station (BS) following an energy-efficient multi-hop fashion. Detailed experimental analysis and simulation results reveal GIICCF increases the performance of any pure cluster-based and chain-based protocols by a huge margin.

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