Secure Satellite Communication Systems Design with Individual Secrecy Rate Constraints

In this paper, we study multibeam satellite secure communication through physical (PHY) layer security techniques, i.e., joint power control and beamforming. By first assuming that the Channel State Information (CSI) is available and the beamforming weights are fixed, a novel secure satellite system design is investigated to minimize the transmit power with individual secrecy rate constraints. An iterative algorithm is proposed to obtain an optimized power allocation strategy. Moreover, sub-optimal beamforming weights are obtained by completely eliminating the co-channel interference and nulling the eavesdroppers' signal simultaneously. In order to obtain jointly optimized power allocation and beamforming strategy in some practical cases, e.g., with certain estimation errors of the CSI, we further evaluate the impact of the eavesdropper's CSI on the secure multibeam satellite system design. The convergence of the iterative algorithm is proven under justifiable assumptions. The performance is evaluated by taking into account the impact of the number of antenna elements, number of beams, individual secrecy rate requirement, and CSI. The proposed novel secure multibeam satellite system design can achieve optimized power allocation to ensure the minimum individual secrecy rate requirement. The results show that the joint beamforming scheme is more favorable than fixed beamforming scheme, especially in the cases of a larger number of satellite antenna elements and higher secrecy rate requirement. Finally, we compare the results under the current satellite air-interface in DVB-S2 and the results under Gaussian inputs.Comment: 34 pages, 10 figures, 1 table, submitted to "Transactions on Information Forensics and Security

Relaying energy allocation in training-based amplify and forward relay communications

We consider relay-assisted communication in a training-based transmission scheme. Each transmission block consists of a training phase and a data transmission phase. The relay node employs the amplify-and-forward protocol during all transmissions. We focus on the relay signaling design and investigate the benefit of allowing for different relaying power during the training phase and the data transmission phase. Specifically, the relaying energy allocation between the two phases is optimized for maximizing the average received signal-to-noise ratio at the destination node. We study this optimization problem for both single-antenna relay and multi-antenna relay and derive a simple closed-form relaying energy allocation strategy that achieves near-optimal performance. This closed-form strategy depends only on the length of the data transmission phase but not on other system parameters such as the relaying energy budget, the number of antennas at the relay, and the distances between the source, relay and destination nodes.This work was supported by the Australian Research Council's Discovery Projects funding scheme (project no. DP0984950, DP110102548) and the Research Council of Norway through the project 197565/V30. The work has been carried out while T. Lamahewa was at the Australian National University

Patterned complex-valued matrix derivatives

A systematic and simple method is proposed for how to find the derivative of complex-valued matrix functions which depend on matrix arguments that contain patterns. The proposed method is developed by means of the chain rule and it is able to handle both linear and nonlinear patterns. One main issue of the proposed method is to Identify a matrix function which depends on independent variables and its domain must have the same dimension as the dimension of the set of patterned matrices. In addition, this function must produce all the matrices within the pattern of interest. Some illustrative examples which are relevant for problems in the area of signal processing for communications are presented. © 2008 IEEE

Algorithm For Jointly Optimized Analysis And Synthesis FIR Filter Banks

An algorithm for jointly optimizing uniform analysis and synthesis FIR filter banks for a given input power spectral density is proposed. The FIR subband coder is optimized with respect to the minimum block mean square error between the output and the input signals under a bit constraint. The subband quantizers are modeled as additive, signal-independent, white noise sources. Illustrative examples showing the system performance as well as filter magnitude and impulse responses are given. The performance results are compared to the rate distortion curves, the performance for the optimal transform coder, and the optimal filter bank with unconstrained length filters. The use of two subbands in a filter bank having filters of length six in all the filters, gives 1.42 dB better system performance compared to a signal-adaptive, linear phase, biorthogonal filter bank, when coding a Gaussian AR(1) source with correlation coefficient 0.95 at 2.75 bits/sample. 1. INTRODUCTION Filter banks are ..

Jointly Optimal Analysis And Synthesis Filter Banks For Bit Constrained Source Coding

A subband coder structure is fully optimized with respect to the minimum block mean squared error between the output and the input signals under a bit constraint. The analysis filter bank structure generates maximally decimated and equal bandwidth subbands. The subband quantizers are modeled as additive noise sources. To simplify the optimization an optimal multiple-input multiple-output system is first derived. Illustrative examples showing the system performance as well as filter transfer functions are given. The performance results are compared to the rate distortion curves. 1. INTRODUCTION The optimization of low-rate subband coders suffers from two deficiencies. Firstly, the commonly used model for the quantizer is not strictly valid. Secondly, when the quantizer noise becomes sufficiently high, the perfect reconstruction property often assigned to the filter banks, is not longer optimal. Some efforts have been undertaken to overcome these obstacles. A simple improvement of the qu..

Linear Solution of the Combined Source- Channel Coding Problem Using Joint Optimal Analysis and Synthesis Filter Banks

A joint source- channel coding system based on linear multirate filter banks is optimized with respect to minimum block mean squared error, while constraining the channel power. A more general discrete-time block based multiple-input multiple-output system is first optimized. From this system analysis and synthesis filter banks solving the joint source- channel coding problem are derived. A joint optimal transmitter and receiver filter bank system is found. Illustrative examples showing the system performance as well as filter transfer functions are given. The performance results are compared to the optimal performance theoretical attainable curves. 1. Introduction Joint source- channel coding is a promising topic in the search for optimal communication systems. This in spite of "Shannon's separation theorem", which states that the source and channel coders can be optimized separately. The reason why there is still hope for improvements in practical systems is that the separation theo..

Unified theory of complex-valued matrix differentiation

A systematic theory is introduced for finding the derivatives of complex-valued matrix functions with respect to a complex-valued matrix variable and the complex conjugate of this variable. In the framework introduced, the differential of the complex-valued matrix function is used to identify the derivatives of this function. Matrix differentiation results are developed for use in signal processing and communications applications. Several other examples are given. ©2007 IEEE