Abstract
In this paper, we propose a simple yet effective modulation classification method for ML-based multi-user detection. We show that the proposed method, which is a simplification of Bayesian likelihood ratio test, can be implemented by modifying the sphere decoding algorithm. As a result, the modulation classification as well as the multi-user detection can be jointly achieved with minimal classification overhead. Simulation results in multi-user detection of high-speed downlink packet access (HSDPA) system show that the proposed method offers considerable performance gain over conventional RAKE and MMSE algorithms.
| Original language | English |
|---|---|
| Title of host publication | IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC |
| Pages | 668-671 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published - 2009 Nov 20 |
| Event | 2009 IEEE 10th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2009 - Perugia, Italy Duration: 2009 Jun 21 → 2009 Jun 24 |
Other
| Other | 2009 IEEE 10th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2009 |
|---|---|
| Country | Italy |
| City | Perugia |
| Period | 09/6/21 → 09/6/24 |
Fingerprint
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Computer Science Applications
- Information Systems
Cite this
Joint modulation classification and multi-user detection using multi-modulation sphere decoding. / Shim, Byonghyo; Kang, Insung.
IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC. 2009. p. 668-671 5161869.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Joint modulation classification and multi-user detection using multi-modulation sphere decoding
AU - Shim, Byonghyo
AU - Kang, Insung
PY - 2009/11/20
Y1 - 2009/11/20
N2 - In this paper, we propose a simple yet effective modulation classification method for ML-based multi-user detection. We show that the proposed method, which is a simplification of Bayesian likelihood ratio test, can be implemented by modifying the sphere decoding algorithm. As a result, the modulation classification as well as the multi-user detection can be jointly achieved with minimal classification overhead. Simulation results in multi-user detection of high-speed downlink packet access (HSDPA) system show that the proposed method offers considerable performance gain over conventional RAKE and MMSE algorithms.
AB - In this paper, we propose a simple yet effective modulation classification method for ML-based multi-user detection. We show that the proposed method, which is a simplification of Bayesian likelihood ratio test, can be implemented by modifying the sphere decoding algorithm. As a result, the modulation classification as well as the multi-user detection can be jointly achieved with minimal classification overhead. Simulation results in multi-user detection of high-speed downlink packet access (HSDPA) system show that the proposed method offers considerable performance gain over conventional RAKE and MMSE algorithms.
UR - http://www.scopus.com/inward/record.url?scp=70449595649&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70449595649&partnerID=8YFLogxK
U2 - 10.1109/SPAWC.2009.5161869
DO - 10.1109/SPAWC.2009.5161869
M3 - Conference contribution
SN - 9781424436965
SP - 668
EP - 671
BT - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
ER -