Amr El-Keyi

Nuzzer: A Large-Scale Device-Free Passive Localization System for Wireless Environments

The widespread usage of WLANs and mobile devices has fostered the interest in localization systems for wireless environments. The majority of research in the context of wireless-based localization systems has focused on device-based active localization, in which devices are attached to tracked entities. Recently, device-free passive localization (DfP) has been proposed where the tracked entity is neither required to carry devices nor to participate actively in the localization process. Previous studies have focused on small areas and/or controlled environments. In this paper, we present the design, implementation, and analysis of Nuzzer, a large-scale DfP localization system, which tracks entities in real environments, rich in multipath. We first present probabilistic techniques for DfP localization of a single entity and evaluate their performance both analytically and in typical office buildings. Our results show that Nuzzer gives location estimates with less than 2-meters median distance error. We then give an algorithm for estimating the number of entities in an area of interest and localizing them into coarse-grained zones to enhance the scalability of the system. This indicates the suitability of Nuzzer to a large number of application domains.

Efficient 3-D placement of an aerial base station in next generation cellular networks

Agility and resilience requirements of future cellular networks may not be fully satisfied by terrestrial base stations in cases of unexpected or temporary events. A promising solution is assisting the cellular network via low-altitude unmanned aerial vehicles equipped with base stations, i.e., drone-cells. Although drone-cells provide a quick deployment opportunity as aerial base stations, efficient placement becomes one of the key issues. In addition to mobility of the drone-cells in the vertical dimension as well as the horizontal dimension, the differences between the air-to-ground and terrestrial channels cause the placement of the drone-cells to diverge from placement of terrestrial base stations. In this paper, we first highlight the properties of the drone-cell placement problem, and formulate it as a 3-D placement problem with the objective of maximizing the revenue of the network. After some mathematical manipulations, we formulate an equivalent quadratically-constrained mixed integer non-linear optimization problem and propose a computationally efficient numerical solution for this problem. We verify our analytical derivations with numerical simulations and enrich them with discussions which could serve as guidelines for researchers, mobile network operators, and policy makers.

Propagation Modeling for Accurate Indoor WLAN RSS-Based Localization

WLAN RSS-based localization has been a hot research topic for the last years. To obtain high accuracy in the noisy wireless channel, WLAN location determination systems usually use a calibration phase, where a radio map, capturing the signal strength signatures at different locations in the area of interest, is built. The radio map construction process takes a lot of time and effort, reducing the value of WLAN localization systems. In this paper, we propose 3D ray tracing as a way for automatically generating a highly accurate radiomap. We compare this method to previously used propagation modeling-based methods like the Wall Attenuation Factor and 2D ray tracing models. We evaluate the performance of each method and its computational cost in a typical residential environment. We also examine the sensitivity of the localization accuracy to inaccurate material parameters. Our results quantify the accuracy- complexity trade-off of the different proposed techniques with 3D ray tracing giving the best localization accuracy compared to measurements with acceptable computational requirements on a typical PC.

Robust adaptive beamforming based on the Kalman filter

In this paper, we present a novel approach to implement the robust minimum variance distortionless response (MVDR) beamformer. This beamformer is based on worst-case performance optimization and has been shown to provide an excellent robustness against arbitrary but norm-bounded mismatches in the desired signal steering vector. However, the existing algorithms to solve this problem do not have direct computationally efficient online implementations. In this paper, we develop a new algorithm for the robust MVDR beamformer, which is based on the constrained Kalman filter and can be implemented online with a low computational cost. Our algorithm is shown to have a similar performance to that of the original second-order cone programming (SOCP)-based implementation of the robust MVDR beamformer. We also present two improved modifications of the proposed algorithm to additionally account for nonstationary environments. These modifications are based on model switching and hypothesis merging techniques that further improve the robustness of the beamformer against rapid (abrupt) environmental changes.

QOS-Constrained Multiuser Peer-to-Peer Amplify-and-Forward Relay Beamforming

A wireless communication scenario is considered with K single-antenna source-destination pairs communicating through several half-duplex amplify-and-forward MIMO relays where each source is targeting only one destination. The relay beamforming matrices are designed in order to minimize the total power transmitted from the relays subject to quality of service constraints on the received signal to interference-plus-noise ratio at each destination node. Due to the nonconvexity of this problem, several approximations have been used in the literature to find a computationally efficient solution. A novel solution technique is developed in which the problem is decomposed into a group of second-order cone programs (SOCPs) parameterized by K phase angles; each associated with one of the constraints. An iterative algorithm is proposed to search for the phase angles and the relay beamforming matrices sequentially. However, convergence to the global optimal beamforming matrices cannot be guaranteed. Two methods for searching for the optimal values of the phase angles are proposed (from which the optimal beamforming matrices can be obtained) using grid search and bisection and the convergence of these methods to the global optimal solution of the problem is proved. Numerical simulations are presented showing the superior performance of the proposed algorithms compared to earlier suboptimal approximations at the expense of a moderate increase in the computational complexity.

Cooperative MIMO-beamforming for multiuser relay networks

In this paper, we develop a beamforming algorithm for multiuser MIMO-relaying wireless systems. We consider a relaying scenario with multiple sources transmitting to one or more destination nodes through several relay terminals. Each relay is equipped with multiple antennas. We jointly design the beamforming matrices of the cooperating relays by minimizing both the noise received at each destination node and the interference caused by the sources not targeting this node. We impose additional constraints that preserve the received signal from each source at its targeted destination node. The relay beamforming problem is shown to be a convex optimization problem and is formulated as a second-order cone program that can be efficiently solved using interior point methods. Numerical simulations are presented showing the superior performance of our beamforming technique compared to previously proposed zero forcing relay beamforming.

Coverage probability analysis for wireless networks using repulsive point processes

The recent witnessed evolution of cellular networks from a carefully planned deployment to more irregular, heterogeneous deployments of Macro, Pico and Femto-BSs motivates new analysis and design approaches. In this paper, we analyze the coverage probability in cellular networks assuming repulsive point processes for the base station deployment. In particular, we characterize, analytically using stochastic geometry, the downlink probability of coverage under a Matern hardcore point process to ensure minimum distance between the randomly located base stations. Assuming a mobile user connects to the nearest base station and Rayleigh fading, we derive two lower bounds expressions on the downlink probability of coverage that is within 4% from the simulated scenario. To validate our model, we compare the probability of coverage of the Matern hardcore topology against an actual base station deployment obtained from a public database. The comparison shows that the actual base station deployment can be fitted by setting the appropriate Matern point process density.

Collaborative Uplink Transmit Beamforming With Robustness Against Channel Estimation Errors

We consider the uplink of collaborative wireless communication systems, where multiple relay terminals decode the signal of a nearby user and forward it to a distant single-antenna base station. We present a collaborative uplink transmit beamforming strategy that can be employed at the relay terminals to provide robustness against uncertainties in the channel state information. The proposed beamforming scheme is obtained using the available knowledge about the second-order statistics of the channel and the possibly erroneous channel state information. The beamforming weight vector is derived by minimizing the total transmitted power subject to a constraint that preserves the received signal at the base station for all the channel realizations within a prescribed uncertainty set. We present two beamforming algorithms based on different mathematical descriptions of the uncertainty set. Both algorithms can be applied to line-of-sight (LOS) propagation and flat-fading channels. In the first algorithm, the robust beamforming vector is computed at the base station using the uplink data and fed back to the cooperating relay terminals. This centralized processing scheme allows any additional convex constraint to be easily incorporated into the beamforming strategy. In the second algorithm, the beamforming vector of each terminal is locally computed using the available knowledge about the terminals channel and a single parameter (Lagrange multiplier) that is broadcast from the base station to all the cooperating terminals. Simulation results are presented, showing the superior performance of our proposed algorithms compared with classical transmit beamforming techniques in both LOS propagation and flat-fading channels.

Adaptive linearly constrained minimum variance beamforming for multiuser cooperative relaying using the kalman filter

In this paper, we consider a wireless communication scenario with multiple source-destination pairs communicating through several cooperative amplify-and-forward relay terminals. The relays are equipped with multiple antennas that receive the source signals and transmit them to the destination nodes. We develop two iterative relay beamforming algorithms that can be applied in real-time. In both algorithms, the relay beamforming matrices are jointly designed by minimizing the received power at all the destination nodes while preserving the desired signal at each destination. The first algorithm requires the existence of a local processing center that computes the beamforming coefficients of all the relays. In the second algorithm, each relay can compute its beamforming coefficients locally with the help of some common information that is broadcasted from the other relays. This is achieved at the expense of enforcing the desired signal preservation constraints non-cooperatively. We provide two extensions of the proposed algorithms that allow the relays to control their transmission power and to modify the quality of service provided to different sources. Simulation results are presented validating the ability of the proposed algorithms to perform their beamforming tasks efficiently and to track rapid changes in the operating environment.

Wideband robust beamforming based on worst-case performance optimization

A novel wideband beam former is proposed with robustness against array response errors. The proposed beam former differs from earlier techniques in that its robustness is directly related to the uncertainties in the array manifold while avoiding the suboptimal subband decomposition approach. The wideband robust beamforming problem is formulated as a second-order cone programming (SOCP) convex optimization problem which can be solved efficiently in polynomial time using interior point methods. Simulation results show an improved performance of the proposed beam-former compared to earlier wideband robust beamforming techniques