Symbiotic Radio: A New Application of Large Intelligent Surface/Antennas (LISA)
To overcome the challenges in achieving extremely high throughput and super-massive access in future wireless communications, in this paper, we focus on a novel large intelligent surfacelantennas (LISA)-assisted symbiotic radio (SR) system. Specifically, in the proposed system, a LISA transmits mess...
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| Published in | IEEE Wireless Communications and Networking Conference : [proceedings] : WCNC pp. 1 - 6 |
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| Main Authors | , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
01.05.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1558-2612 |
| DOI | 10.1109/WCNC45663.2020.9120455 |
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| Summary: | To overcome the challenges in achieving extremely high throughput and super-massive access in future wireless communications, in this paper, we focus on a novel large intelligent surfacelantennas (LISA)-assisted symbiotic radio (SR) system. Specifically, in the proposed system, a LISA transmits messages to its destination by using backscatter communication, and at the same time, it assists the transmission from a base station (BS) to its user by intelligently reconfiguring the wireless environment. In this paper, we are interested in the joint active (BS) and passive (LISA) beamforming design problem to maximize the transmission rate of LISA subject to the BS transmission rate constraint. Due to the non-convexity of the problem, we first relax the rank-one constraint based on the technique of semi-definite relaxation (SDR) and then decouple that optimization problem into two subproblems based on the block coordinate descent (BCD) method, each of which is a convex problem. Due to the expectation terms in the constraints, we propose two algorithms called the Lagrangian algorithm and approximate algorithm to address it. Finally, simulation results are presented to validate the effectiveness of the proposed algorithms and the superiority of the proposed system. |
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| ISSN: | 1558-2612 |
| DOI: | 10.1109/WCNC45663.2020.9120455 |