Towards Energy Neutrality in Energy Harvesting Wireless Sensor Networks: A Case for Distributed Compressive Sensing?

This paper advocates the use of the emerging distributed compressive sensing (DCS) paradigm in order to deploy energy harvesting (EH) wireless sensor networks (WSN) with practical network lifetime and data gathering rates that are substantially higher than the state-of-the-art. In particular, we argue that there are two fundamental mechanisms in an EH WSN: i) the energy diversity associated with the EH process that entails that the harvested energy can vary from sensor node to sensor node, and ii) the sensing diversity associated with the DCS process that entails that the energy consumption can also vary across the sensor nodes without compromising data recovery. We also argue that such mechanisms offer the means to match closely the energy demand to the energy supply in order to unlock the possibility for energy-neutral WSNs that leverage EH capability. A number of analytic and simulation results are presented in order to illustrate the potential of the approach.Comment: 6 pages. This work will be presented at the 2013 IEEE Global Communications Conference (GLOBECOM), Atlanta, US, December 201

Can Punctured Rate-1/2 Turbo Codes Achieve a Lower Error Floor than their Rate-1/3 Parent Codes?

In this paper we concentrate on rate-1/3 systematic parallel concatenated convolutional codes and their rate-1/2 punctured child codes. Assuming maximum-likelihood decoding over an additive white Gaussian channel, we demonstrate that a rate-1/2 non-systematic child code can exhibit a lower error floor than that of its rate-1/3 parent code, if a particular condition is met. However, assuming iterative decoding, convergence of the non-systematic code towards low bit-error rates is problematic. To alleviate this problem, we propose rate-1/2 partially-systematic codes that can still achieve a lower error floor than that of their rate-1/3 parent codes. Results obtained from extrinsic information transfer charts and simulations support our conclusion.Comment: 5 pages, 7 figures, Proceedings of the 2006 IEEE Information Theory Workshop, Chengdu, China, October 22-26, 200

On the analogy between vehicle and vehicle-like cavities with reverberation chambers

Deploying wireless systems in vehicles is an area of current interest. Often, it is implicitly assumed that the electromagnetic environment in vehicle cavities is analogous to that in reverberation chambers, it is therefore important to assess to what extent this analogy is valid. Specifically, the cavity time constant, electromagnetic isolation and electric field uniformity are investigated for typical vehicle and vehicle-like cavities. It is found that the time constant is a global property of the cavity (i.e., it is the same for all links). This is important, as it means that the root mean square delay spread for any link is also a property of the cavity, and thus so is the coherence bandwidth. These properties could be exploited by wireless sytems deployed in vehicles. It is also found that the field distribution is not homogeneous (and is therefore not uniform), but can be isotropic. For situations where the field distribution is isotropic, the spatial coherence is well defined, and therefore Multiple-Input-Multiple-Output antenna arrays can be used to improve performance of wireless systems. For situations where the field distribution is not isotropic, the angular spread is not uniform, and therefore beam-forming can be used to improve performance of wireless systems.This is the author's accepted manuscript and will be under embargo until publication. The final version is available from IEEE at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=692843

Joint Sensing Matrix and Sparsifying Dictionary Optimization for Tensor Compressive Sensing.

Tensor compressive sensing (TCS) is a multidimensional framework of compressive sensing (CS), and it is advantageous in terms of reducing the amount of storage, easing hardware implementations, and preserving multidimensional structures of signals in comparison to a conventional CS system. In a TCS system, instead of using a random sensing matrix and a predefined dictionary, the average-case performance can be further improved by employing an optimized multidimensional sensing matrix and a learned multilinear sparsifying dictionary. In this paper, we propose an approach that jointly optimizes the sensing matrix and dictionary for a TCS system. For the sensing matrix design in TCS, an extended separable approach with a closed form solution and a novel iterative nonseparable method are proposed when the multilinear dictionary is fixed. In addition, a multidimensional dictionary learning method that takes advantages of the multidimensional structure is derived, and the influence of sensing matrices is taken into account in the learning process. A joint optimization is achieved via alternately iterating the optimization of the sensing matrix and dictionary. Numerical experiments using both synthetic data and real images demonstrate the superiority of the proposed approache

Characterizing the spectral properties and time variation of the in-vehicle wireless communication channel

To deploy effective communication systems in vehicle cavities, it is critical to understand the time variation of the in-vehicle channel. Initially rapid channel variation is addressed, which is characterised in the frequency domain as a Doppler spread. It is then shown that for typical Doppler spreads, the in-vehicle channel is underspread, and therefore the information capacity approaches the capacity achieved with perfect receiver channel state information in the infinite bandwidth limit. Measurements are performed for a number of channel variation scenarios (absorptive motion, reflective motion, one antenna moving, both antennas moving), at a number of carrier frequencies and for a number of cavity loading scenarios. It is found that the Doppler spread increases with carrier frequency, however the type of channel variation and loading appear to have little effect. Channel variation over a longer time period is also measured, to characterise the slower channel variation. Channel variation is a function of the cavity occupant motion, which is difficult to model theoretically, therefore an empirical model for the slow channel variation is proposed, which leads to an improved estimate of the channel state.This work is supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) and National Physical Laboratory (NPL) under an EPSRC-NPL Industrial CASE studentship programme on the subject of intra-Vehicular Wireless Sensor Networks. The work of T. H. Loh was supported by the 2009 - 2012 Physical Program and 2012 - 2015 Electromagnetic Metrology Program of the National Measurement Office, an Executive Agency of the U.K. Department for Business, Innovation and Skills, under Projects 113860 and EMT13020, respectively.This is the author accepted manuscript. The final version can be found on the publisher's website at: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=682581

How to Measure the Average and Peak Age of Information in Real Networks?

The Age of information (AoI) was proposed in the literature to quantify the freshness of information. The majority of the work done in this area has theoretically evaluated AoI and its Peak (PAoI). In this paper, a method for obtaining the value of AoI and PAoI from experiments is proposed. We conducted an experiment emulating an M/M/1 queue and used the proposed method to evaluate AoI and PAoI. The values were compared to the expressions presented previously in the literature. Our results show that the proposed method is accurate for the M/M/1 queue. A statistical test was conducted to confirm the reliability of this conclusion