Afzal, A, Feki, A, Debbah, M et al. (3 more authors) (2017) Leveraging D2D Communication to Maximize the Spectral Efficiency of Massive MIMO Systems. In: 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt). Workshop on Spatial Stochastic Models for Wireless Networks (SpaSWiN), 19 May 2017, Paris, France. IEEE ISBN 978-3-9018-8290-6
Abstract
In this paper, we investigate offloading of UEs in D2D mode for a massive MIMO system, where the base station (BS) is equipped with a large, but finite number of antennas and the total number of UEs is kept fixed. We derive closedform expressions for the bounds of the overall capacity of the system. Our results reveal that there exists an optimal user offload fraction, which maximizes the overall capacity. This fraction is strongly coupled with the network parameters such as the number of antennas at the BS, D2D link distance and the transmit SNR at both the UE and the BS. Given a set of network parameters, careful tuning of the offload fraction can provide up to 5× capacity gains.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2017 IFIP. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Device-to-device communication, MIMO, Interference, Antennas, Signal to noise ratio, Transmitters, Conferences |
Dates: |
|
Institution: | The University of Leeds |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Jun 2017 10:32 |
Last Modified: | 16 Jan 2018 06:20 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.23919/WIOPT.2017.7959929 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:117232 |