TY  - JOUR
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018458467&doi=10.1007%2fs13369-017-2730-9&partnerID=40&md5=0a2cb264ae6831710a852e3b5554770d
A1  - Bahloul, M.R.
A1  - Yusoff, M.Z.
A1  - Abdel-Aty, A.-H.
A1  - Saad, M.N.
A1  - Laouiti, A.
N1  - cited By 3
Y1  - 2017///
VL  - 42
JF  - Arabian Journal for Science and Engineering
ID  - scholars8113
EP  - 5209
N2  - In this paper, an efficient and reliable feature-fusion-based modulation classification (MC) algorithm for multiple-input multiple-output (MIMO) systems is developed. It uses two higher-order cumulants of the transmitted signal streams to classify a broad set of modulation types with no prior knowledge of the channel state information. We address the problem of the soft-decision fusion for the feature-fusion-based MC algorithms for MIMO systems and introduce an optimal soft-decision fusion scheme to find the classification result. The complexity order of the proposed MC algorithm is studied in detail to demonstrate its low computation cost, and its performance is validated extensively by simulation results to show its practical effectiveness. © 2017, King Fahd University of Petroleum & Minerals.
SN  - 2193567X
IS  - 12
TI  - Efficient and Reliable Modulation Classification for MIMO Systems
PB  - Springer Verlag
SP  - 5201
AV  - none
ER  -