.png){kind=icon}
.png){kind=icon}
Return
Minimum Error Pursuit Algorithm for Symbol Detection in MBM Massive-MIMO
.png){kind=icon}
PRE
AI
DOI：10.1109/LCOMM.2020.3029004.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Media-based modulation (MBM) with massive multiple-input multiple-output (mMIMO) wireless systems is a viable solution to realize the ever-increasing demand for high-speed data and extensive connectivity in beyond 5G and 6G wireless communications. MBM-mMIMO utilizes less transmit power and radio resources measured against mMIMO to yield high spectral efficiency and high data rate. However, symbol detection in the uplink of MBM-mMIMO is challenging due to the sparse nature of the received signal, and the cumulative effect of inter-user interference and noise. In this letter, support recovery error constraint-based low complexity sequential symbol detection technique is proposed for uplink MBM-mMIMO system. The proposed MBM-mMIMO detection technique exploits the upper bound on support recovery error and iteratively minimizes the residual error associated with the estimated transmit vector. A reduced message space is also introduced to further enrich the exploration capability of the proposed technique. Simulation results reveal the viability of proposed techniques over several state-of-the-art MBM-mMIMO detection techniques as BER performance and computational complexity are concerned.
Keywords:
Uplink
Modulation
Radio frequency
Mirrors
Wireless communication
Transmitting antennas
Space exploration
Massive MIMO
MBM
support recovery
maximum likelihood
error refinement
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.4
Papers:
1.3W
Citations:
2.2W