Malar, E (2021) Optimal Microwave Wireless Backhaul Link Design Using a Massive MIMO for 5G HetNet-Practical Deployment Scenario. Wireless Personal Communications, 120 (3). pp. 2117-2133. ISSN 0929-6212
Full text not available from this repository.Abstract
The massive multiple-input–multiple-output that enhances energy efficiency and spectral efficiency is the primary technology for fifth generation wireless networks. A move toward heterogeneous elements such as microcells, femtocells, picocells as well as remote radio heads, characterised by physical measurements, backhauls, transmission and propagation, is now underway to ensure an economical transition to the cellular network infrastructure, that is far from expensive high power mounted base stations. This adaptation presents many obstacles to network operations and co-existence. The proposed work therefore provides a design for a 28 GHz microwave wireless backhaul link for small cell base stations (SBSs) as well as the number of antennas required for the base station (BS) to achieve a target backhaul rate of 10 Gbit/s within a given transmit power of 40 dBm. In this work a distributed beamforming algorithm is formulated in a multi-cell scenario using methods from random matrix theory, under the assumption that the system dimensions are large. The design purpose is to minimize the total transmit power over all BSs according to the constraints of the signal-to-interference-and-noise ratio (SINR) as beamformers are integrated in a distributed manner. The BSs may only need to share the channel statistics in the suggested algorithm, instead of the instant channel state information. The simulation results show that the proposed algorithm strongly satisfies the target SINR constraints as the number of SBSs per cell grows high.
Item Type: | Article |
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Subjects: | C Computer Science and Engineering > Wireless Network C Computer Science and Engineering > Mobile Network E Electronics and Communication Engineering > Antennas |
Divisions: | Electrical and Electronics Engineering |
Depositing User: | Users 5 not found. |
Date Deposited: | 18 Apr 2024 08:06 |
Last Modified: | 18 Apr 2024 08:06 |
URI: | https://ir.psgitech.ac.in/id/eprint/352 |