Tharaka A. Lamahewa

Propagation Models for Body-Area Networks: A Survey and New Outlook

This article is a review of wireless body-area network (BAN) channel models, with observations about the selection of the best channel model in terms of both first- and second-order statistics. Particular insight into the dominant factors that affect propagation for body-area networks is given. Important second-order statistical measures are discussed, where coherence times and fade durations are of particular interest. The IEEE 802.15.6 standard is used as a basis for the review, with observations and insights given about body-area networks. In this context, narrowband and ultra-wideband (UWB) models are summarized for different measurement environments and carrier frequencies. On-body, in-body, and off-body propagation models are discussed where appropriate. In general, lognormal fading or gamma fading models of the body-area network channel are most applicable. A goodness-of-fit criterion that directly trades off model error and complexity is presented, which gives a new outlook for channel modeling. By this new outlook it is demonstrated that through significant simplification of individual link propagation models for body-area networks, it is possible to combine link models with only a few parameters. Common misconceptions regarding the appropriateness of applying traditional path-loss measures to these short-range networks are then exposed. Finally, the use of relays, which is an option in IEEE 802.15.6, is shown to be important for maintaining reliability in various body-area-network propagation scenarios.

A Gaussian-Sum Based Cubature Kalman Filter for Bearings-Only Tracking

Herein is presented an efficient nonlinear filtering algorithm called the Gaussian-sum cubature Kalman filter (GSCKF) for the bearings-only tracking problem. It is developed based on the recently proposed cubature Kalman filter and is built within a Gaussian-sum framework. The new algorithm consists of a splitting and merging procedure when a high degree of nonlinearity is detected. Simulation results show that the proposed algorithm demonstrates comparable performance to the particle filter (PF) with significantly reduced computational cost.

Open-source testbed for Body Area Networks: 200 sample/sec, 12 hrs continuous measurement

We present the design criteria and specifications of a novel Open-Source hardware channel sounder and Open-Source data sets for measurements of the Body Area Channel at the 2400MHz ISM band and 2360MHz band. We outline a need for open hardware and measurement data to facilitate robust standardization of the new Body Area Networks. We demonstrate typical analyses on a public data set, with reference to previous works, and show how complex network topologies may be simulated through simple real measurements using reciprocity.

Simple Prediction-Based Power Control for the On-Body Area Communications Channel

Methods for transmit power control based on simple long-term channel prediction for the general body-area communications channel are presented. The power control methods are based on large sets of empirical every-day activity data. Numerous transmit-receive pair (Tx-Rx) locations on the human body, i.e. on-body, for a typical body-area-network (BAN) are considered. With the use of a simple prediction method based on held samples, and an enhanced held simple prediction method that uses short term mean path loss with the held sample, optimal power allocation for long-term transmit power control is described. When tested, according to the draft IEEE 802.15.6 BAN radio standard, on empirical data, both power allocation methods are shown to be more reliable, and also more energy efficient in terms of transmit circuit power consumption, than systems that use typical set Tx power levels for BAN.

Two-way training: optimal power allocation for pilot and data transmission

In this letter, we consider multiple-input single-output (MISO) systems with two-way training based transmission. We focus on the long-term system performance and study the optimal power allocation between reverse training, forward training and data transmission. We derive closed-form solutions for the optimal power allocation using high signal-to-noise ratio (SNR) approximations, and show that they achieve near optimal performance in terms of symbol error rate (SER) for different modulation schemes over a wide range of SNR values.

On azimuthally symmetric 2-sphere convolution

We consider the problem of azimuthally symmetric convolution of signals defined on the 2-Sphere. Applications of such convolution include but are not limited to: geodesy, astronomical data (such as the famous Wilkinson Microwave Anisotropy Probe data), and 3D beamforming/sensing. We review various definitions of convolution from the literature and show a nontrivial equivalence between different definitions. Some convolution formulations based on SO(3) are shown not to be well formed for applications and we demonstrate a simpler framework to understand, use and generalize azimuthally symmetric convolution.

Kalman filter-based channel estimation for amplify and forward relay communications

We propose an autoregressive model for the combined amplify and forward time-varying relay channel and derive a causal iterative channel estimation method using Kalman filter. This formulation enables us to study and compare two widely-used pilot transmission strategies in terms of the channel estimation errors. We provide a single-letter formula for the power allocation between the source and relay to achieve near optimal bit error rate (BER) performance in dual-hop communications. For cooperative communications, we show that the relay speed has a significant impact on the BER performance, and hence is important to be considered in practical system design.

On Lower Bounding the Information Capacity of Amplify and Forward Wireless Relay Channels with Channel Estimation Errors

We formulate a capacity lower bound for the dual-hop wireless relay channel which employs an amplify-and-forward (AF) protocol at the relay node. In AF relaying, even when the fading channel in both hops is complex Gaussian distributed, the overall dual-hop channel is non-Gaussian. WPe highlight that there is a fundamental difference between Gaussian and non-Gaussian channels in terms of deriving their capacity lower bound. Specifically for non-Gaussian channels, the channel estimation error variance depends on the received pilot signal and is, in general, different from the average error variance. Whereas for Gaussian distributed channels, which have been predominantly studied in the literature, the channel estimation error variance conditioned on the observed pilot signal coincides with the average error variance. We provide an example using the AF dual-hop channel to exhibit the numerical difference between the true capacity lower bound and that obtained by using the average instead of the conditional error variance.

Multiple Target Localization Using Wideband Echo Chirp Signals

Active target detection and localization is a classical signal processing problem that arises in various military and biomedical applications. A novel method for the detection and estimation of the range, velocity and direction of arrival (DOA) of multiple far-field targets using wideband chirp signals is proposed in this paper. Using the plane wave representation of the signals reflected from far-field targets, a modal preprocessing procedure is designed for the echo signals received at a concentric circular array. Following that, the parameter estimation method for the multiple targets present is developed based on (i) the fractional Fourier transform which projects a signal onto an orthonormal basis formed by chirps and (ii) the Root-MUSIC algorithm which is a high resolution DOA estimation method originally proposed for narrowband signals received at a uniform linear array. There is no limit on the number of targets detectable by the proposed method as long as the echo signals are separable in the chosen fractional Fourier domain. Simulation results show that the proposed method demonstrates good performance, with low root-mean-square errors in the parameters estimated under difficult conditions such as closely spaced targets and low signal-to-noise ratio.

Design Guidelines for Training-Based MIMO Systems With Feedback

In this paper, we study the optimal training and data transmission strategies for block fading multiple-input multiple-output (MIMO) systems with feedback. We consider both the channel gain feedback (CGF) system and the channel covariance feedback (CCF) system. Using an accurate capacity lower bound as a figure of merit that takes channel estimation errors into account, we investigate the optimization problems on the temporal power allocation to training and data transmission as well as the training length. For CGF systems without feedback delay, we prove that the optimal solutions coincide with those for nonfeedback systems. Moreover, we show that these solutions stay nearly optimal even in the presence of feedback delay. This finding is important for practical MIMO training design. For CCF systems, the optimal training length can be less than the number of transmit antennas, which is verified through numerical analysis. Taking this fact into account, we propose a simple yet near optimal transmission strategy for CCF systems, and derive the optimal temporal power allocation over pilot and data transmission.