NDLI: Compressive Feedback Based on Sparse Approximation for Multiuser MIMO Systems

Content Provider	IEEE Xplore Digital Library
Author	Hyungjoon Song Woohyun Seo Daesik Hong
Copyright Year	1967
Abstract	In multiuser multiple-input-multiple-output (MU-MIMO) systems, limited feedback schemes using a vector quantization codebook (VQC) for partial channel state information (CSI) can enable a base station (BS) to enhance the sum throughput at low feedback rates. However, the VQC has a limited throughput gain, although it requires a great deal of memory and complexity as the feedback rate increases. Therefore, we propose a high-precision feedback technique by using sparse approximation and compression called ¿compressive feedback (CF).¿ By using the sparse approximation with a unitary codebook and the compression via a ¿good¿ compression matrix, CF achieves greater sum throughput than VQC. Our analysis of the maximum achievable sum rate verifies the superiority of CF over VQC.
Sponsorship	IEEE Vehicular Technology Society
Starting Page	1017
Ending Page	1023
Page Count	7
File Size	414893
File Format	PDF
ISSN	00189545
Volume Number	59
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	MIMO Throughput Array signal processing State feedback Vector quantization Base stations Sparse matrices Information technology Matching pursuit algorithms Feeds multiuser multiple-input–multiple-output (MU-MIMO) Compressive sampling limited feedback
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Automotive Engineering Computer Networks and Communications Electrical and Electronic Engineering Aerospace Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Low-Feedback-Rate and Low-Complexity Downlink Multiuser MIMO Systems

Multi-User MIMO with Limited Feedback Using Alternating Codebooks

Downlink Multiuser MIMO Systems With Adaptive Feedback Rate

Spherical-Cap Approximation of Vector Quantization for Quantization-Based Combining in MIMO Broadcast Channels with Limited Feedback

On channel quantization and feedback strategies for multiuser MIMO-OFDM downlink systems

Limited feedback-based block diagonalization for the MIMO broadcast channel

Joint Transmit and Receive Beamforming for Multiuser MIMO Downlinks With Channel Uncertainty

Efficient MIMO Scheduling Algorithms With a Fixed-Time Allocation Ratio

Two-Phase Multiuser Scheduling for Multiantenna Downlinks Exploiting Reduced Finite-Rate Feedback

Compressive Feedback Based on Sparse Approximation for Multiuser MIMO Systems

Similar Documents

Low-Feedback-Rate and Low-Complexity Downlink Multiuser MIMO Systems

Multi-User MIMO with Limited Feedback Using Alternating Codebooks

Downlink Multiuser MIMO Systems With Adaptive Feedback Rate

Spherical-Cap Approximation of Vector Quantization for Quantization-Based Combining in MIMO Broadcast Channels with Limited Feedback

On channel quantization and feedback strategies for multiuser MIMO-OFDM downlink systems

Limited feedback-based block diagonalization for the MIMO broadcast channel

Joint Transmit and Receive Beamforming for Multiuser MIMO Downlinks With Channel Uncertainty

Efficient MIMO Scheduling Algorithms With a Fixed-Time Allocation Ratio

Two-Phase Multiuser Scheduling for Multiantenna Downlinks Exploiting Reduced Finite-Rate Feedback

Compressive Feedback Based on Sparse Approximation for Multiuser MIMO Systems