NDLI: On the optimization of lattice reduction-based approximate MAP detection using randomized sampling in MIMO systems

Content Provider	IEEE Xplore Digital Library
Author	Lin Bai Qiaoyu Li Jinho Choi Yu Quan
Copyright Year	2013
Description	Author affiliation: Inst. of China Electron. Syst. Eng. Corp., Beijing, China (Yu Quan) \|\| Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China (Lin Bai; Qiaoyu Li) \|\| Sch. of Inf. & Commun., Gwangju Insitute of Sci. & Technol. (GIST), Gwangju, South Korea (Jinho Choi)
Abstract	For iterative detection and decoding (IDD) in multiple-input multiple-output (MIMO) systems, the maximum a posteriori probability (MAP) detection is desirable to maximize the performance. Unfortunately, the MAP detection usually requires a prohibitively high computational complexity. In this paper, a lattice reduction (LR)-based MIMO detection method is proposed to achieve near MAP performance with reasonably low complexity in IDD, where the a priori information (API) is taken into account during list generation using randomized sampling to improve the performance. The sampling distribution is optimized to maximize the probability of sampling the MAP solution. It is shown that the proposed method outperforms conventional LR-based ones, where no API is considered during the list generation. Furthermore, a trade-off between performance and complexity is exploited with different list lengths.
Starting Page	136
Ending Page	140
File Size	239122
Page Count	5
File Format	PDF
ISBN	9781479906987
DOI	10.1109/ICTC.2013.6675324
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-14
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article

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

Lattice Reduction-Based MIMO Iterative Receiver Using Randomized Sampling

An improved detection algorithm based on Lattice reduction for MIMO system

Improved lattice reduction aided detection based on extended noise variance matrix for MIMO systems

Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice reduction

Near-Maximum Likelihood Detection of MIMO Systems Using Error Detection Scheme Based Lattice Reduction

Lattice reduction aided detection in large-MIMO systems

A Sequential Detection Approach for Approximate MAP Detection in MIMO Systems

Lattice-Reduction-Aided Conditional Detection for MIMO Systems

Lattice Reduction-Based Approximate MAP Detection with Bit-Wise Combining and Integer Perturbed List Generation

On the optimization of lattice reduction-based approximate MAP detection using randomized sampling in MIMO systems

Similar Documents

Lattice Reduction-Based MIMO Iterative Receiver Using Randomized Sampling

An improved detection algorithm based on Lattice reduction for MIMO system

Improved lattice reduction aided detection based on extended noise variance matrix for MIMO systems

Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice reduction

Near-Maximum Likelihood Detection of MIMO Systems Using Error Detection Scheme Based Lattice Reduction

Lattice reduction aided detection in large-MIMO systems

A Sequential Detection Approach for Approximate MAP Detection in MIMO Systems

Lattice-Reduction-Aided Conditional Detection for MIMO Systems

Lattice Reduction-Based Approximate MAP Detection with Bit-Wise Combining and Integer Perturbed List Generation

On the optimization of lattice reduction-based approximate MAP detection using randomized sampling in MIMO systems