MIMO IBC beamforming with combined channel estimate and covariance CSIT

2017 ◽  
Author(s):  
Wassim Tabikh ◽  
Dirk Slock ◽  
Yi Yuan-Wu
Keyword(s):  
Channel Estimate ◽  
Combined Channel

Combined Channel and Spatial Attention for YOLOv5 during Target Detection

2021 ◽  
Author(s):  
Guihui Shi ◽  
Jiezhong Huang ◽  
Junhua Zhang ◽  
Guoqin Tan ◽  
Gaoli Sang
Keyword(s):  
Spatial Attention ◽  
Target Detection ◽  
Combined Channel

Code design for combined channel estimation and error protection

2002 ◽  
Vol 48 (5) ◽  
pp. 1162-1171 ◽  
Author(s):  
M. Skoglund ◽  
J. Giese ◽  
S. Parkvall
Keyword(s):  
Channel Estimation ◽  
Code Design ◽  
Error Protection ◽  
Combined Channel

scholarly journals Robust Beamforming Design for SWIPT-Based Multi-Radio Wireless Mesh Network with Cooperative Jamming

Information ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 138
Author(s):  
Liang Li ◽  
Xiongwen Zhao ◽  
Suiyan Geng ◽  
Yu Zhang ◽  
Lei Zhang
Keyword(s):  
Wireless Mesh Network ◽  
Mesh Networks ◽  
Mesh Network ◽  
Channel State ◽  
Sdp Relaxation ◽  
Cooperative Jamming ◽  
Total Transmission ◽  
Channel Estimate ◽  
Wireless Mesh ◽  
The Individual

Wireless mesh networks (WMNs) can provide flexible wireless connections in a smart city, internet of things (IoT), and device-to-device (D2D) communications. The performance of WMNs can be greatly enhanced by adopting a multi-radio technique, which enables a node to communicate with more nodes simultaneously. However, multi-radio WMNs face two main challenges, namely, energy consumption and physical layer secrecy. In this paper, both simultaneous wireless information and power transfer (SWIPT) and cooperative jamming technologies were adopted to overcome these two problems. We designed the SWIPT and cooperative jamming scheme, minimizing the total transmission power by properly selecting beamforming vectors of the WMN nodes and jammer to satisfy the individual signal-to-interference-plus-noise ratio (SINR) and energy harvesting (EH) constrains. Especially, we considered the channel estimate error caused by the imperfect channel state information. The SINR of eavesdropper (Eve) was suppressed to protect the secrecy of WMN nodes. Due to the fractional form, the problem was proved to be non-convex. We developed a tractable algorithm by transforming it into a convex one, utilizing semi-definite programming (SDP) relaxation and S-procedure methods. The simulation results validated the effectiveness of the proposed algorithm compared with the non-robust design.

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