The paper first provides a general overview on the existing probabilistic‐driven methods aimed at convexifying the secrecy rate maximisation problem. Challenges and requirements of the procedures are fully taken into consideration for multiinput multioutput multiantenna eavesdropper wiretap channels. The problem constrained by an outage probability for the pure Ergodic capacity (perfect secrecy defined by Shannon) is analytically solved. Such analytical solution is performed robustly, something that originates principally from our imperfect statistical knowledge of the wiretap channel at the transmitter. Then, solely concentrating on McDiarmid inequality, we also extend our previous work to propose 2 new approaches. The bounds of our represented schemes are obviously accurate, tight, and achievable, something that effectively guarantee the system to overcome the probable challenges, eg, correlation in multiinput multioutput antenna arrays. Furthermore, the procedures are straightforwardly compared with each other from standpoint of complexity. Results are technically conducted to assure us about the proposed methods' merits, merely defining the significantly more favourable asymptotic bounds and the less resultant complexities. In particular, our proposed approaches sensibly outperform all the procedures, per se, something that can be accordingly assigned for other ergodic equilibria.

Adaptive controllers and signal processors play a key role in dealing with parameter uncertainties. This paper proposes an adaptive and new information theoretic algorithm for secure and optimal source-coding. We optimise the volume of the achievable rate-distortion-equivocation region by the private Helen's rate (HR), defining a stochastic mean-field game (MFG). The aforementioned stochasticity deals with the additional uncoded side-information (SI) at the encoder-decoder, or even possibly-decoded SI at the eavesdropper (Eve). The stochastic partial derivative equations (SPDEs), namely the Hamilton-Jacobi-Bellman (HJB) and the Fokker-Planck-Kolmogorov (FPK) are presented, being solved by a discretised Lagrangian. We explore the Information-flow over the resultant Riemann-Sphere and our proposed SMFG's stability from a many-body-theoretic perspective. We also show that while the equivocation (uncertainty) rate is ≤ min{H(X), R h }, I(Y; Z|W) which is upper-bounded to min{I(X ; Y), I(Y; Z|W)}, versus I(X ; Z|W) theoretically converges to the information-Bottleneck-bound H(X). Simulation results also show an out-performance of our scheme over the existing work, proving the SMFG's stability and an adequate distance to Pareto-Optimal sets. Our generic solution covers a comprehensive field of studies determining smooth non-linearity.

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Two closed-form solutions for the approximation bound in relation to resource allocation for multiple-input multiple-output (MIMO)-based cognitive radio systems are provided. The design problem is actualized in the underlay scenario for a single-user strategy. The concentration is mainly on the Ergodic capacity constrained by an outage probability at the secondary receiver, regarding our imperfect knowledge of the interference channel at the transmitter.

A probability-theoretic problem under information constraints for the concept of optimal control over a noisymemoryless channel is considered. For our Observer-Controller block, i.e., the lossy joint-source-channel-coding (JSCC) scheme, after providing the relative mathematical expressions, we propose a Blahut-Arimoto-type algorithm − which is, to the best of our knowledge, for the first time. The algorithm efficiently finds the probability-mass-functions (PMFs) required for min. This problem is an N P−hard and non-convex multi-objective optimisation (MOO) one, were the objective functions are respectively the distortion function dim Null I( Ŝ; S → ∞ and the memorylesschannel capacity dim Null I(X; X → 0. Our novel algorithm applies an Alternating optimisation method. Subsequently, a robust version of the algorithm is discussed with regard to the perturbed PMFs − parameter uncertainties in general.The aforementioned robustness is actualised by exploiting the simultaneous-perturbation-stochastic-approximation (SPSA). The principles of detectability-and-stabilisability as well as synchronisability are explored, in addition to providing the simulationsby which the efficiency of our work is shown. We also calculate the total complexity of our proposed algorithms respectively as O T K M 0 K log K and O T K M 0 K log K + 0.33K . Our methodology is generic which can be applied to other fields of studies which are optimisation-driven.

Abstract-A new scheme for MIMO CDMA-based optical satellite communications (OSATCOMs) is presented. Three independent problems are described for up-link and downlink in terms of two distinguished optimization problems. At first, in up-link, Pulse-width optimization is proposed to reduce dispersions over fibers as the terrestrial part. This is performed for return-to-zero (RZ) modulation that is supposed to be used as an example in here. This is carried out by solving the first optimization problem, while minimizing the probability of overlapping for the Gaussian pulses that are used to produce RZ. Some constraints are assumed such as a threshold for the peak-to-average power ratio (PAPR). In down-link, the second and the third problems are discussed as follows, jointly as a closed-form solution. Solving the second optimization problem, an objective function is obtained, namely the MIMO CDMA-based satellite weight-matrix as a conventional adaptive beam-former. The Satellite link is stablished over flat un-correlated Nakagami-m/Suzuki fading channels as the second problem. On the other hand, the mentioned optimization problem is robustly solved as the third important problem, while considering inter-cell interferences in the multi-cell scenario. Robust solution is performed due to the partial knowledge of each cell from the others in which the link capacity is maximized. Analytical results are conducted to investigate the merit of system.

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The Letter proposes a precise mathematical expression for game theory-based multiple-input multiple-output (MIMO) cognitive radio systems. The sum of information rates and the network utility are maximized, providing an accurate examination. Constraining the interference signals caused by the secondary transmitters on the primary receivers in the underlay scenario also needs to be addressed.