scholarly journals Secrecy capacity optimization artificial noise: the ergodic secrecy capacity lower bound and optimal power allocation

2020 ◽  
Author(s):  
Yebo Gu ◽  
Zhilu Wu ◽  
Zhendong Yin ◽  
Bowen Huang
Keyword(s):  
Lower Bound ◽  
Channel Estimation ◽  
Closed Form ◽  
Power Allocation ◽  
Estimation Error ◽  
Closed Form Expression ◽  
Artificial Noise ◽  
Secrecy Capacity ◽  
Capacity Optimization ◽  
Form Expression

Abstract The secure transmission problem of MIMO wireless system in fading channels is studied in this paper. We add a secrecy capacity optimization artificial noise(SCO-AN) to the transported signal for improving the security performance of the system. The closed-form expression of secrecy capacity's lower bound is obtained. Base on the closed-form expression of secrecy capacity's lower bound, We optimize the power allocation between the information-bearing signal and the SCO-AN. By calculating, the optimal ratio of power alloation betwenn the information-bearing signal and the SCO-AN is obtained. Through simulation, the results shows the secrecy capacity increases with more receiving antennas and less eavesdropping antennas.And more power should be allocated to the SCO-AN with the increase of the colluding eavedroppers.More over, we study the effect of channel estimation error on power allocation between information-bearing signal and SCO-AN and find that more power should be allocated to decrease eavesdroppers capacity if the channel estimation is not perfect.

scholarly journals Power Allocation for Secrecy-Capacity-Optimization-Artificial-Noise Secure MIMO Precoding Systems under Perfect and Imperfect Channel State Information

2021 ◽  
Vol 11 (10) ◽  
pp. 4558
Author(s):  
Yebo Gu ◽  
Bowen Huang ◽  
Zhilu Wu
Keyword(s):  
Channel Estimation ◽  
Power Allocation ◽  
Optimization Problem ◽  
Estimation Error ◽  
Channel Estimation Error ◽  
Artificial Noise ◽  
Secrecy Capacity ◽  
Transmission Power ◽  
Channel State ◽  
Imperfect Channel Estimation

In this paper, we consider the physical layer security problem of the wireless communication system. For the multiple-input, multiple-output (MIMO) wireless communication system, secrecy capacity optimization artificial noise (SCO−AN) is introduced and studied. Unlike its traditional counterpart, SCO−AN is an artificial noise located in the range space of the channel state information space and thus results in a significant increase in the secrecy capacity. Due to the limitation of transmission power, making rational use of this power is crucial to effectively increase the secrecy capacity. Hence, in this paper, the objective function of transmission power allocation is constructed. We also consider the imperfect channel estimation in the power allocation problems. In traditional AN research conducted in the past, the expression of the imperfect channel estimation effect was left unknown. Still, the extent to which the channel estimation error impacts the accuracy of secrecy capacity computation is not negligible. We derive the expression of channel estimation error for least square (LS) and minimum mean squared error (MMSE) channel estimation. The objective function for transmission power allocation is non-convex. That is, the traditional gradient method cannot be used to solve this non-convex optimization problem of power allocation. An improved sequence quadratic program (ISQP) is therefore applied to solve this optimization problem. The numerical result shows that the ISQP is better than other algorithms, and the power allocation as derived from ISQP significantly increases secrecy capacity.

Reliability optimization for non-repairable series-parallel systems with a choice of redundancy strategies and heterogeneous components: Erlang time-to-failure distribution

2020 ◽  
pp. 1748006X2095257
Author(s):  
Meisam Sadeghi ◽  
Emad Roghanian ◽  
Hamid Shahriari ◽  
Hassan Sadeghi
Keyword(s):  
Lower Bound ◽  
Closed Form ◽  
System Reliability ◽  
Parallel Systems ◽  
Closed Form Expression ◽  
Erlang Distribution ◽  
Time To Failure ◽  
Form Expression ◽  
Integrodifference Equation ◽  
Cold Standby

The redundancy allocation problem (RAP) of non-repairable series-parallel systems considering cold standby components and imperfect switching mechanism has been traditionally formulated with the objective of maximizing a lower bound on system reliability instead of exact system reliability. This objective function has been considered due to the difficulty of determining a closed-form expression for the system reliability equation. But, the solution that maximizes the lower bound for system reliability does not necessarily maximize exact system reliability and thus, the obtained system reliability may be far from the optimal reliability. This article attempts to overcome the mentioned drawback. Under the assumption that component time-to-failure is distributed according to an Erlang distribution and switch time-to-failure is exponentially distributed, a closed-form expression for the subsystem cold standby reliability equation is derived by solving an integrodifference equation. A semi-analytical expression is also derived for the reliability equation of a subsystem with mixed redundancy strategy. The accuracy and the correctness of the derived equations are validated analytically. Using these equations, the RAP of non-repairable series-parallel systems with a choice of redundancy strategies is formulated. The proposed mathematical model maximizes exact system reliability at mission time given system design constraints. Unlike most of the previous formulations, the possibility of using heterogeneous components in each subsystem is provided so that the active components can be of one type and the standby ones of the other. The results of an illustrative example demonstrate the high performance of the proposed model in determining optimal design configuration and increasing system reliability.

scholarly journals Impact of Uncertain Channel Estimation and Outdated Feedback on the Adaptive M-PSK Modulation

2014 ◽  
Vol 10 (1) ◽  
pp. 51
Author(s):  
Mohamed L. Ammari ◽  
Francois Gagnon
Keyword(s):  
Channel Estimation ◽  
Estimation Error ◽  
Error Variance ◽  
Channel Estimation Error ◽  
Closed Form Expression ◽  
Modulation Scheme ◽  
Form Expression ◽  
Pilot Symbols ◽  
Modulation Techniques ◽  
Modulation Level

This paper investigates an adaptive M-ary phaseshiftkeying (M-PSK) modulation scheme over Rayleigh flatfading channels. The data rate is adapted according to thechannel state. At the receiver, the fading is estimated using pilot symbols. To cancel the channel impact, we correct the received signal by dividing it by the estimated value of the fading. So, we propose to adjust the modulation level by examining the statistics of the corrected signal. In contrast to the previous works on the adaptive M-PSK modulation techniques, our modulation switching protocol takes into account the channel estimation error variance. Moreover, we derive a new closed-form expression for the average bit error rate of the considered system.

scholarly journals Physical-Layer Security Analysis over M-Distributed Fading Channels

Entropy ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. 998 ◽  
Author(s):  
Sheng-Hong Lin ◽  
Rong-Rong Lu ◽  
Xian-Tao Fu ◽  
An-Ling Tong ◽  
Jin-Yuan Wang
Keyword(s):  
Lower Bound ◽  
Closed Form ◽  
Fading Channels ◽  
Physical Layer Security ◽  
Physical Layer ◽  
Exact Expression ◽  
Closed Form Expression ◽  
Secrecy Outage Probability ◽  
Secrecy Capacity ◽  
Special Cases

In this paper, the physical layer security over the M-distributed fading channel is investigated. Initially, an exact expression of secrecy outage probability (SOP) is derived, which has an integral term. To get a closed-form expression, a lower bound of SOP is obtained. After that, the exact expression for the probability of strictly positive secrecy capacity (SPSC) is derived, which is in closed-form. Finally, an exact expression of ergodic secrecy capacity (ESC) is derived, which has two integral terms. To reduce its computational complexity, a closed-from expression for the lower bound of ESC is obtained. As special cases of M-distributed fading channels, the secure performance of the K, exponential, and Gamma-Gamma fading channels are also derived, respectively. Numerical results show that all theoretical results match well with Monte-Carlo simulation results. Specifically, when the average signal-to-noise ratio of main channel is larger than 40 dB, the relative errors for the lower bound of SOP, the probability of SPSC, and the lower bound of ESC are less than 1.936%, 6.753%, and 1.845%, respectively. This indicates that the derived theoretical expressions can be directly used to evaluate system performance without time-consuming simulations. Moreover, the derived results regarding parameters that influence the secrecy performance will enable system designers to quickly determine the optimal available parameter choices when facing different security risks.

scholarly journals Asymptotic Performance Analysis of the MUSIC Algorithm for Direction-of-Arrival Estimation

2020 ◽  
Vol 10 (6) ◽  
pp. 2063
Author(s):  
So-Hee Jeong ◽  
Byung-kwon Son ◽  
Joon-Ho Lee
Keyword(s):  
Performance Analysis ◽  
Closed Form ◽  
Covariance Matrix ◽  
Estimation Error ◽  
Closed Form Expression ◽  
Simultaneous Estimation ◽  
Music Algorithm ◽  
Form Expression ◽  
Sample Covariance ◽  
Future Work

We consider the performance analysis of the multiple signal classification (MUSIC) algorithm for multiple incident signals when the uniform linear array (ULA) is adopted for estimation of the azimuth of each incident signal. We derive closed-form expression of the estimation error for each incident signal. After some approximations, we derive closed-form expression of the mean square error (MSE) for each incident signal. In the MUSIC algorithm, the eigenvectors of covariance matrix are used for calculation of the MUSIC spectrum. Our derivation is based on how the eigenvectors of the sample covariance matrix are related to those of the true covariance matrix. The main contribution of this paper is the reduction in computational complexity for the performance analysis of the MUSIC algorithm in comparison with the traditional Monte–Carlo simulation-based performance analysis. The validity of the derived expressions is shown using the numerical results. Future work includes an extension to performance analysis of the MUSIC algorithm for simultaneous estimation of the azimuth and the elevation.

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