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Register a new userErgodic Secrecy Rate of Antenna-Selection-Aided MIMOME Channels with BPSK/QPSK Modulations
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Chongjun Ouyang
Publication date
2019
fields
Electronic Engineering
and research's language is
English
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This paper analyzes transmit antenna selection (TAS) under Rayleigh flat fading for BPSK/QPSK modulations in multiple-input multiple-output wiretap channels, also termed as multiple-input multiple-output multiple-eavesdropper (MIMOME) channels. In our protocol, a single antenna is selected to transmit the secret message and selection combing (SC) or maximal-ratio combing (MRC) is utilized at the legitimate receiver or the eavesdropper. Novel closed-form expressions for the ergodic secrecy rates are derived to approximate the exact values, which hold high precision and compact forms. Besides theoretical derivations, simulations are provided to demonstrate the feasibility and validity of the proposed formulas.
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This paper studies the secrecy performance of multiple-input multiple-output (MIMO) wiretap channels, also termed as multiple-input multiple-output multiple-eavesdropper (MIMOME) channels, under transmit antenna selection (TAS) and BPSK/QPSK modulations. In the main channel between the transmitter and the legitimate receiver, a single transmit antenna is selected to maximizes the instantaneous Signal to Noise Ratio (SNR) at the receiver. At the receiver and the eavesdropper, selection combination (SC) is utilized. By assuming Rayleigh flat fading, we first derive the closed-form approximated expression for the ergodic secrecy rate when the channel state information of the eavesdropper (CSIE) is available at the transmitter. Next, analytical formulas for the approximated and asymptotic secrecy outage probability (SOP) are also developed when CSIE is unavailable. Besides theoretical derivations, simulation results are provided to demonstrate the approximation precision of the derived results. Furthermore, the asymptotic results reveal that the secrecy diversity order degrades into 0 due to the finitealphabet inputs, which is totally different from that driven by the Gaussian inputs.
This paper studies the performance of single-input multiple-output (SIMO) systems under receive antenna selection (RAS) and BPSK/QPSK modulations. At the receiver, a subset of branches are selected and combined using maximal-ratio combining (MRC) to maximize the instantaneous Signal to Noise Ratio (SNR). By assuming independent and identical distributed (i.i.d.) Rayleigh flat fading, a closed-form expression, with considerably high precision, is developed to approximate the average input-output mutual information, also termed as symmetric capacity, of the whole system. Later, this approximated expression is further utilized to investigate the efficient capacity and energy efficiency of the SIMO system under BPSK/QPSK modulations and RAS. Besides analytical derivations, simulations are provided to demonstrate the approximation precision, feasibility and validity of the derived results.
Ambient Backscatter Communication (AmBC) is an emerging communication technology that can enable green Internet-of-Things deployments. The widespread acceptance of this paradigm is limited by low Signal-to-Interference-Plus-Noise Ratio (SINR) of the signal impinging on the receiver antenna due to the strong direct path interference and unknown ambient signal. The adverse impact of these two factors can be mitigated by using non-coherent multi-antenna receivers, which is known to require higher SINR to reach Bit-Error-Rate (BER) performance of coherent receivers. However, in literature, coherent receivers for AmBC systems are little-studied because of unknown ambient signal, unknown location of AmBC tags, and varying channel conditions. In this paper, a coherent multi-antenna receiver, which does not require a prior information of the ambient signal, for decoding Binary-Phase-shift-Keying (BPSK) modulated signal is presented. The performance of the proposed receiver is compared with the ideal coherent receiver that has a perfect phase information, and also with the performance of non-coherent receiver, which assumes distributions for ambient signal and phase offset caused by excess length of the backscatter path. Comparative simulation results show the designed receiver can achieve the same BER-performance of the ideal coherent receiver with 1-dB more SINR, which corresponds to 5-dB or more gain with respect to non-coherent reception of On-Off-Keying modulated signals. Variation of the detection performance with the tag location shows that the coverage area is in the close vicinity of the transmitter and a larger region around the receiver, which is consistent with the theoretical results.
Inspired by the remarkable learning and prediction performance of deep neural networks (DNNs), we apply one special type of DNN framework, known as model-driven deep unfolding neural network, to reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) single-input multiple-output (SIMO) systems. We focus on uplink cascaded channel estimation, where known and fixed base station combining and RIS phase control matrices are considered for collecting observations. To boost the estimation performance and reduce the training overhead, the inherent channel sparsity of mmWave channels is leveraged in the deep unfolding method. It is verified that the proposed deep unfolding network architecture can outperform the least squares (LS) method with a relatively smaller training overhead and online computational complexity.
We investigate transmission optimization for intelligent reflecting surface (IRS) assisted multi-antenna systems from the physical-layer security perspective. The design goal is to maximize the system secrecy rate subject to the source transmit power constraint and the unit modulus constraints imposed on phase shifts at the IRS. To solve this complicated non-convex problem, we develop an efficient alternating algorithm where the solutions to the transmit covariance of the source and the phase shift matrix of the IRS are achieved in closed form and semi-closed forms, respectively. The convergence of the proposed algorithm is guaranteed theoretically. Simulations results validate the performance advantage of the proposed optimized design.
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