Ehsan Zandi

A Modified Levenberg–Marquardt Method for the Bidirectional Relay Channel

This paper presents an optimization approach for a system consisting of multiple bidirectional links over a two-way amplify-and-forward relay. Improvement to the fairness of the system is desired. All user pairs exchange information over one relay station (RS) with multiple antennas. Due to the joint transmission to all users, the users are subject to mutual interference. A mitigation of the interference can be achieved by max-min fair precoding optimization where the relay is subject to a sum power constraint. The resulting optimization problem is nonconvex. This paper proposes a novel iterative low-complexity approach based on a modified Levenberg-Marquardt (LM) method to find near optimal solutions. The presented method finds solutions close to the standard convex-solver-based relaxation approach.

Adaptive Control in Cyber-Physical Systems: Distributed Consensus Control for Wireless Cyber-Physical Systems

Abstract In contrast to cable-bound connections, the wireless channel is an unreliable medium. Moreover, in distributed control, where multiple agents interact, a low latency in communication is important for a fast convergence of the distributed control algorithms. In this chapter, we present a tutorial of the theory of consensus in multiagent systems targeting wireless cyber-physical systems (CPS). Particularly, we address communication engineers. Additionally, we present how consensus can be achieved with a given communication topology and we discuss how a limited communication capacity on different communication links influences the consensus of such CPS. As the quality of the wireless channel strongly influences the convergence of distributed control algorithms, we also present medium access control layer scheduling algorithms to reduce the latency and increase robustness in case of weak channel conditions.

Power allocation for multi-target sensor networks

This paper regards a network of wireless passive sensors, suitable for radar applications. The network observes multiple number of target signals to be estimated. We propose an unbiased estimator whose error is minimized by optimizing both the power allocation at sensor nodes and the fusion coefficients at the fusion center. Since the underlying optimization problems are subject to both the individual power constraints of sensor nodes and a sum-power constraint of the sensor network, the corresponding solution describes an optimized policy for efficient power allocation to the sensor nodes and enables an energy-aware operation of the sensor network. The results are compared via numerical simulations.

Power allocation for multi-target multi-fusion-rule sensor networks

In this paper we study a wireless passive sensor network. The sensors are deployed to estimate the true values of multiple active target signals. The sensors forward their observation to a fusion center, which processes the observation of each sensor by a set of fusion rules. One achievement of this paper is proposing an unbiased estimator with minimized variance of errors. To do so, we optimize both the power allocation to the sensor nodes and the fusion rules. The optimal solution to the fusion rules are attained analytically, while the power allocation is solved sub-optimally. Finally, our results are reinforced by numerical simulations.

Power allocation for orthogonally-observed multi-target sensor networks

In this paper we study the performance bound of a wireless sensor network which is capable of estimating the true values of several active targets. We assume that sensors can observe each target separately, assuming either targets are orthogonal in frequency or physically distinguishable. The aforementioned assumption is of practical relevance for targets with different physical nature, e.g., heat, humidity, pressure etc. Another interesting example of separable observation is power grids where the voltage of each node can be exclusively estimated at any of its neighboring nodes by measuring the flowing current and applying the Ohms law. Even though such a sensor network is not wireless, the current work provides a suitable framework for state estimation and planning of the smart meters in smart grids. We then propose a novel unbiased estimator. Moreover, as an additional design variable, we perform power allocation and optimal fusion of data to further improve the performance of the proposed estimator. The optimal fusion rules are provided in closed-form, while power allocation is optimally done by means of convex optimization.

Optimal linear MMSE design for passive distributed radar sensor network systems

In this paper we present optimal power allocation, together with optimal linear signal fusion, considering a passive distributed radar sensor network system. The goal of a passive distributed radar is to obtain a reliable estimation from a source signal, by collecting and combining the individual observations from the network of sensor nodes (SN)s in a fusion center (FC). In this respect, a linear minimum-mean-square-error (MMSE) optimization strategy is considered, where optimal linear operation at the SNs as well as the FC are obtained analytically. The obtained solutions are then analytically and numerically compared to the previously studied unbiased linear MMSE (ULMMSE) approach. It is observed that both schemes share the same strategy for the optimal power allocation among the SNs, but differ in the corresponding linear fusion. As expected, the proposed approach reaches a lower estimation MSE compared to the ULMMSE one.

Fast power control for amplify-and-forward multiple-antenna bidirectional relays

Cooperative relay communication is an interesting area of research, since it is to enhance data rate and coverage in wireless networks. In this paper, we propose a method to optimize power allocation strategy in an amplify-and-forward relay system. Our objective is to attain a max-min fairness within co-channel users. To reduce the complexity we maximize the upper bound on the performance. The reason is that this bound is observed to be tight in low noise conditions. Therefore, one achievement of this work is separating the problem of relay pre-coding design from power allocation. Then, the power control is done iteratively via the proposed low-complexity algorithm whose convergence is proven. The relay precoder can be subsequently designed via existing methods, such as semidefinite programming, nonetheless, it is beyond the main focus of the current work. The optimality of the proposed power allocation algorithm is very hard to mathematically prove. Yet, the simulation results are promising.

Estimating the scattering distribution of the received signals in multipath fading channels

This paper presents a novel approach for estimating the distribution of the incoming waves at the mobile unit antenna, i.e. the scattering distribution, in a typical micro-cellular system. This estimate is vital in determining many system parameters of interest as well as designing unbiased estimators for the velocity of mobile units in micro-cellular systems. The proposed approach deploys the zero-crossing rates of the quadrature components and the instantaneous frequency of the received signal at the mobile unit to estimate the scattering distribution. We also propose a new model for simulating multipath fading channels with non-isotropic scattering. We use the channel simulator to evaluate the performance of the proposed estimator for the scattering distribution. Simulation results show that proposed estimator exhibits small bias and root mean square error.