NDLI: On Quantization for Masked Beamforming Secrecy Systems

Content Provider	IEEE Xplore Digital Library
Author	Chia-Hua Lin Shang-Ho Tsai Yuan-Pei Lin
Copyright Year	2002
Abstract	This study investigates how to quantize the masked beamforming systems to maximize the secrecy rate for MISOSE (multiple-input, single-output, single-eavesdropper) channels and assume that this eavesdropper equipped with only single antenna, where only partial channel state information (CSI) at the legitimate receiver is available to the transmitter. In this case, the artificial noise (AN) leaks to the legitimate receiver due to CSI quantization. In the literature, all quantization bits are used to quantize the beamforming vector. Then the null space of this quantized beamforming vector is used to transmit the AN. We find that such quantization schemes can result in serious interference at the legitimate receiver. To overcome this issue, we propose that the beamforming vector and the AN vector should be quantized separately, where the beamforming vector should be selected from a codebook to maximize the beamforming gain and the AN vector should be selected from another codebook to minimize the leakage (or interference). Theoretical results show that separate quantization can significantly reduce the AN leakage at the legitimate receiver. Furthermore, based on the proposed quantization scheme, we show how to allocate bits to separately quantize the beamforming vector and the AN vector to maximize the secrecy rate. By using the proposed quantization and bit allocation schemes, the secrecy rates of masked beamforming systems can be improved compared to the conventional quantization schemes. Simulation results corroborate the theoretical results.
Starting Page	5616
Ending Page	5628
Page Count	13
File Size	1124563
File Format	PDF
ISSN	15361276
Volume Number	14
Issue Number	10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Receivers Array signal processing Quantization (signal) Transmitters Interference Wireless communication Null space codebook and secrecy rate Artificial-noise masked beamforming MISOSE quantization
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering Computer Science Applications

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