arXiv subjects

Robert Piechocki

Publications and source records attributed to Robert Piechocki.

32 records · Page 2Linked to original sources

arXiv2018

Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable

In this paper we study the prediction of heart rate from acceleration using a wrist worn wearable. Although existing photoplethysmography (PPG) heart rate sensors provide reliable measurements, they use considerably more energy than accelerometers and have a major impact on battery life of wearable devices. By using energy-efficient accelerometers to predict heart rate, significant energy savings can be made. Further, we are interested in understanding patient recovery after a heart rate intervention, where we expect a variation in heart rate over time. Therefore, we propose an online approach to tackle the concept as time passes. We evaluate the methods on approximately 4 weeks of free living data from three patients over a number of months. We show that our approach can achieve good predictive performance (e.g., 2.89 Mean Absolute Error) while using the PPG heart rate sensor infrequently (e.g., 20.25% of the samples).

stat.AP↗

arXiv2017

Exploiting WiFi Channel State Information for Residential Healthcare Informatics

Detection and interpretation of human activities have emerged as a challenging healthcare problem in areas such as assisted living and remote monitoring. Besides traditional approaches that rely on wearable devices and camera systems, WiFi based technologies are evolving as a promising solution for indoor monitoring and activity recognition. This is, in part, due to the pervasive nature of WiFi in residential settings such as homes and care facilities, and unobtrusive nature of WiFi based sensing. Advanced signal processing techniques can accurately extract WiFi channel status information (CSI) using commercial off-the-shelf (COTS) devices or bespoke hardware. This includes phase variations, frequency shifts and signal levels. In this paper, we describe the healthcare application of Doppler shifts in the WiFi CSI, caused by human activities which take place in the signal coverage area. The technique is shown to recognize different types of human activities and behaviour and be very suitable for applications in healthcare. Three experimental case studies are presented to illustrate the capabilities of WiFi CSI Doppler sensing in assisted living and residential care environments. We also discuss the potential opportunities and practical challenges for real-world scenarios.

eess.SP↗

arXiv2017

Agile Calibration Process of Full-Stack Simulation Frameworks for V2X Communications

Computer simulations and real-world car trials are essential to investigate the performance of Vehicle-to-Everything (V2X) networks. However, simulations are imperfect models of the physical reality and can be trusted only when they indicate agreement with the real-world. On the other hand, trials lack reproducibility and are subject to uncertainties and errors. In this paper, we will illustrate a case study where the interrelationship between trials, simulation, and the reality-of-interest is presented. Results are then compared in a holistic fashion. Our study will describe the procedure followed to macroscopically calibrate a full-stack network simulator to conduct high-fidelity full-stack computer simulations.

cs.PF↗

arXiv2016

Interference Management in Heterogeneous Networks with Blind Transmitters

Future multi-tier communication networks will require enhanced network capacity and reduced overhead. In the absence of Channel State Information (CSI) at the transmitters, Blind Interference Alignment (BIA) and Topological Interference Management (TIM) can achieve optimal Degrees of Freedom (DoF), minimising network's overhead. In addition, Non-Orthogonal Multiple Access (NOMA) can increase the sum rate of the network, compared to orthogonal radio access techniques currently adopted by 4G networks. Our contribution is two interference management schemes, BIA and a hybrid TIM-NOMA scheme, employed in heterogeneous networks by applying user-pairing and Kronecker Product representation. BIA manages inter- and intra-cell interference by antenna selection and appropriate message scheduling. The hybrid scheme manages intra-cell interference based on NOMA and inter-cell interference based on TIM. We show that both schemes achieve at least double the rate of TDMA. The hybrid scheme always outperforms TDMA and BIA in terms of Degrees of Freedom (DoF). Comparing the two proposed schemes, BIA achieves more DoF than TDMA under certain restrictions, and provides better Bit-Error-Rate (BER) and sum rate performance to macrocell users, whereas the hybrid scheme improves the performance of femtocell users.

cs.IT↗

arXiv2015

Distributed Wideband Spectrum Sensing

We consider the problem of reconstructing wideband frequency spectra from distributed, compressive measurements. The measurements are made by a network of nodes, each independently mixing the ambient spectra with low frequency, random signals. The reconstruction takes place via local transmissions between nodes, each performing simple statistical operations such as ridge regression and shrinkage.

cs.IT↗

arXiv2015

A hybrid TIM-NOMA scheme for the SISO Broadcast Channel

Future mobile communication networks will require enhanced network efficiency and reduced system overhead due to their user density and high data rate demanding applications of the mobile devices. Research on Blind Interference Alignment (BIA) and Topological Interference Management (TIM) has shown that optimal Degrees of Freedom (DoF) can be achieved, in the absence of Channel State Information (CSI) at the transmitters, reducing the network's overhead. Moreover, the recently emerged Non-Orthogonal Multiple Access (NOMA) scheme suggests a different multiple access approach, compared to the current orthogonal methods employed in 4G networks, resulting in high capacity gains. Our contribution is a hybrid TIM-NOMA scheme in Single-Input-Single-Output (SISO) K-user cells, in which users are divided into T groups, and 1/T DoF is achieved for each user. By superimposing users in the power domain, we introduce a two-stage decoding process, managing 'inter-group' interference based on the TIM principles, and 'intra-group' interference based on Successful Interference Cancellation (SIC), as proposed by NOMA. We show that for high SNR values the hybrid scheme can improve the sum rate by at least 100% when compared to Time Division Multiple Access (TDMA).

cs.IT↗

arXiv2014

The capacity of non-identical adaptive group testing

We consider the group testing problem, in the case where the items are defective independently but with non-constant probability. We introduce and analyse an algorithm to solve this problem by grouping items together appropriately. We give conditions under which the algorithm performs essentially optimally in the sense of information-theoretic capacity. We use concentration of measure results to bound the probability that this algorithm requires many more tests than the expected number. This has applications to the allocation of spectrum to cognitive radios, in the case where a database gives prior information that a particular band will be occupied.

cs.IT↗

arXiv2014

Blind Interference Alignment in General Heterogeneous Networks

Heterogeneous networks have a key role in the design of future mobile communication networks, since the employment of small cells around a macrocell enhances the network's efficiency and decreases complexity and power demand. Moreover, research on Blind Interference Alignment (BIA) has shown that optimal Degrees of Freedom (DoF) can be achieved in certain network architectures, with no requirement of Channel State Information (CSI) at the transmitters. Our contribution is a generalised model of BIA in a heterogeneous network with one macrocell with K users and K femtocells each with one user, by using Kronecker (Tensor) Product representation. We introduce a solution on how to vary beamforming vectors under power constraints to maximize the sum rate of the network and how optimal DoF can be achieved over K+1 time slots.

cs.IT↗

arXiv2012

Delay-rate tradeoff in ergodic interference alignment

Ergodic interference alignment, as introduced by Nazer et al (NGJV), is a technique that allows high-rate communication in n-user interference networks with fast fading. It works by splitting communication across a pair of fading matrices. However, it comes with the overhead of a long time delay until matchable matrices occur: the delay is q^n^2 for field size q. In this paper, we outline two new families of schemes, called JAP and JAP-B, that reduce the expected delay, sometimes at the cost of a reduction in rate from the NGJV scheme. In particular, we give examples of good schemes for networks with few users, and show that in large n-user networks, the delay scales like q^T, where T is quadratic in n for a constant per-user rate and T is constant for a constant sum-rate. We also show that half the single-user rate can be achieved while reducing NGJV's delay from q^n^2 to q^(n-1)(n-2). This extended version includes complete proofs and more details of good schemes for small n.

cs.IT↗

arXiv2012

Combinatorial Channel Signature Modulation for Wireless ad-hoc Networks

In this paper we introduce a novel modulation and multiplexing method which facilitates highly efficient and simultaneous communication between multiple terminals in wireless ad-hoc networks. We term this method Combinatorial Channel Signature Modulation (CCSM). The CCSM method is particularly efficient in situations where communicating nodes operate in highly time dispersive environments. This is all achieved with a minimal MAC layer overhead, since all users are allowed to transmit and receive at the same time/frequency (full simultaneous duplex). The CCSM method has its roots in sparse modelling and the receiver is based on compressive sampling techniques. Towards this end, we develop a new low complexity algorithm termed Group Subspace Pursuit. Our analysis suggests that CCSM at least doubles the throughput when compared to the state-of-the art.

cs.IT↗

arXiv2012

Approximate Message Passing under Finite Alphabet Constraints

In this paper we consider Basis Pursuit De-Noising (BPDN) problems in which the sparse original signal is drawn from a finite alphabet. To solve this problem we propose an iterative message passing algorithm, which capitalises not only on the sparsity but by means of a prior distribution also on the discrete nature of the original signal. In our numerical experiments we test this algorithm in combination with a Rademacher measurement matrix and a measurement matrix derived from the random demodulator, which enables compressive sampling of analogue signals. Our results show in both cases significant performance gains over a linear programming based approach to the considered BPDN problem. We also compare the proposed algorithm to a similar message passing based algorithm without prior knowledge and observe an even larger performance improvement.

cs.IT↗

arXiv2011

Non-parametric change-point detection using string matching algorithms

Given the output of a data source taking values in a finite alphabet, we wish to detect change-points, that is times when the statistical properties of the source change. Motivated by ideas of match lengths in information theory, we introduce a novel non-parametric estimator which we call CRECHE (CRossings Enumeration CHange Estimator). We present simulation evidence that this estimator performs well, both for simulated sources and for real data formed by concatenating text sources. For example, we show that we can accurately detect the point at which a source changes from a Markov chain to an IID source with the same stationary distribution. Our estimator requires no assumptions about the form of the source distribution, and avoids the need to estimate its probabilities. Further, we establish consistency of the CRECHE estimator under a related toy model, by establishing a fluid limit and using martingale arguments.

math.PR↗

arXiv2010

Asymptotic Sum-Capacity of Random Gaussian Interference Networks Using Interference Alignment

We consider a dense n-user Gaussian interference network formed by paired transmitters and receivers placed independently at random in Euclidean space. Under natural conditions on the node position distributions and signal attenuation, we prove convergence in probability of the average per-user capacity C_Sigma/n to 1/2 E log(1 + 2SNR). The achievability result follows directly from results based on an interference alignment scheme presented in recent work of Nazer et al. Our main contribution comes through the converse result, motivated by ideas of `bottleneck links' developed in recent work of Jafar. An information theoretic argument gives a capacity bound on such bottleneck links, and probabilistic counting arguments show there are sufficiently many such links to tightly bound the sum-capacity of the whole network.

cs.IT↗

arXiv2009

Interference alignment-based sum capacity bounds for random dense Gaussian interference networks

We consider a dense $K$ user Gaussian interference network formed by paired transmitters and receivers placed independently at random in a fixed spatial region. Under natural conditions on the node position distributions and signal attenuation, we prove convergence in probability of the average per-user capacity $\csum/K$ to $\half \ep \log(1 + 2 \SNR)$. The achievability result follows directly from results based on an interference alignment scheme presented in recent work of Nazer et al. Our main contribution comes through an upper bound, motivated by ideas of `bottleneck capacity' developed in recent work of Jafar. By controlling the physical location of transmitter--receiver pairs, we can match a large proportion of these pairs to form so-called $ε$-bottleneck links, with consequent control of the sum capacity.

cs.IT↗