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Applications delivered by the internet of things have the potential to increase operational efficiency, reliability and safety. However, a challenge exists to deliver connectivity to industries with remote operations at a cost, battery life and form factor that is able to close the business case for deployment. This is especially true in cases where the system must scale to support large numbers of devices. Typical applications include sensor telemetry, low-value asset tracking, and device monitoring and control. Myriota provides global reach for the internet of things by securely delivering high-value small-data direct to a constellation of low Earth orbit satellites. This paper provides an overview of the Myriota communications architecture, and the process taken to transfer Myriota foundation technology into a highly scalable commercial product and service. Recent results from customer facing pilot deployments are also presented.

Myriota is a satellite communications company that specializes in sending small packets of data at ultralow cost from anywhere on Earth. Myriota provides Internet of Things (IoT) services in locations where terrestrial providers cannot profitably operate, including such locations as oceans and the Australian outback. This article provides an overview of the company's global IoT platform.

IEEE Multi-hop relaying is well-known to extend the range of wireless communications. However, the end-to-end performance of the multi-hop relaying channel degrades compared to that observed at the first hop. This performance degradation mainly arises due to i) half-duplex loss and ii) hopping or relaying loss. In this paper, we analyse the degradation in outage probability and ergodic capacity due to hopping loss in a multiple-input multiple-output (MIMO) dual-hop decode-andforward (DF) relaying network over Rayleigh fading channels. In particular, we characterise analytically the performance degradation by deriving closed-form approximations of ergodic capacity and outage probability in the single-source single-relay singleuser, single-source multiple-relay single-user, and single-source single-relay multiple-user topologies. These approximations also provide insights on how to overcome performance degradations due to hopping loss. Moreover, we show that cooperative relaying schemes can recover a significant portion of the hopping loss. Refereed/Peer-reviewed

In systems with parallel analogue-to-digital converters (ADC), diversity combining can improve the signal to noise ratio (SNR) of the digitised signal. We consider a novel architecture, where the parallel ADCs operate on differently attenuated signals, in conjunction with maximal ratio combining and gain weighted combining. Both schemes reduce the effective quantization noise and provide significant SNR improvements over a single ADC and signal averaging, which takes the unweighted average of the ADC output signals. The key to achieving these SNR gains is to carefully select branch attenuations that lead to negative correlation of the quantization noise across branches. Refereed/Peer-reviewed

We consider least squares estimators of carrier phase and amplitude from a noisy communications signal that contains both pilot signals, known to the receiver, and data signals, unknown to the receiver. We focus on signaling constellations that have symbols evenly distributed on the complex unit circle, i.e., M-ary phase shift keying. We show, under reasonably mild conditions on the distribution of the noise, that the least squares estimator of carrier phase is strongly consistent and asymptotically normally distributed. However, the amplitude estimator is asymptotically biased and converges to a positive real number that is a function of the true carrier amplitude, the noise distribution and the size of the constellation. This appears to be the first time that the statistical properties of a non-data-aided estimator for carrier amplitude have been analyzed theoretically. The results of Monte Carlo simulations are provided and these agree with the theoretical results. Refereed/Peer-reviewed

We develop an estimator of time offset (or time-of-arrival) of a transmitted communications signal that contains both pilot symbols, known to the receiver, and data symbols, unknown to the receiver. We focus on signalling constellations that have symbols lying on the complex unit circle, such as M-ary phase shift keying (M-PSK). We describe an algorithm for computing the estimator that requires O(L log L) operations in the worst case, where L is the number of transmitted symbols. Our estimator integrates information from the pilot symbols more effectively than popular estimators from the literature that usually split estimation into two subproblems called symbol timing and frame synchronisation. Our estimator combines these subproblems into a single operation, that of estimating time offset. We hypothesise that our estimator will be statistically more accurate. Monte-Carlo simulations support this hypothesis. Refereed/Peer-reviewed

Polynomial-phase signals have applications including radar, sonar, biology, and radio communication. Of practical importance is the estimation of the parameters of a polynomial phase signal from a sequence of noisy observations. Assuming that the noise is additive and Gaussian, the direct evaluation of the Cramér–Rao lower bound for this estimation problem involves evaluating the inverse of a matrix. Computing this inverse is numerically difficult for polynomial phase signals of large order. By making use of a family of orthogonal polynomials, we derive formulae for the Cramér–Rao bounds that are numerically stable and easy to compute. Refereed/Peer-reviewed

It is well-known that relaying can extend the communication range. However, the performance of the relaying network is inferior compared to a single-hop system where the destination is placed hypothetically at the relay. The gap between the single-hop and relay network, dubbed the multi-hopping or relaying loss, is studied in this paper. In particular, we investigate the increase in outage probability and the degradation in ergodic capacity incurred due to the multi-hopping loss in a dualhop multiple-input multiple-output decode-and-forward relaying network operating in the single-source single-relay single-user topology. Moreover, we show that a cooperative relaying scheme, called the best relay scheme, in the single-source K-relays single-user topology can recover a significant portion of the multi-hopping loss. In both topologies, we derive closed-form approximations for the outage probability and ergodic capacity using the well-known Gaussian approximation Refereed/Peer-reviewed

Multibeam satellite communication (SatCom) with full or aggressive frequency re-use is one of the most promising candidates for next-generation high throughput satellite systems. However, frequency re-use creates interbeam interference which needs to be managed using multiuser precoding techniques in the forward link and multiuser detection techniques in the reverse link. This work considers the forward link of multibeam Sat-Com systems and proposes a novel zero-forcing (ZF) precoding technique that makes use of users' physical location and antenna radiation pattern available at the gateway. Contrary to conventional precoding techniques in multibeam SatCom systems, the proposed precoding technique does not require feedback from user terminals. Numerical results show that the proposed ZF precoder achieves higher ergodic capacity than the conventional ZF precoder. We provide a closed-form approximation for the ergodic capacity of the proposed ZF precoder under rain fading. We also provide a closed-form approximation for computing the moments of the rain fading attenuation which enables us to derive high and low signal-to-noise ratio (SNR) expressions of the ergodic capacity in closed-form. Furthermore, an upper bound on the ergodic capacity is obtained. Monte Carlo simulations are used to validate the accuracy of our analysis. Refereed/Peer-reviewed

We consider the problem of estimating the distance, or range, between two locations by measuring the phase of multiple sinusoidal signals transmitted between the locations. Traditional estimators developed for optical interferometry include the beat wavelength and excess fractions methods. More recently, estimators based on the Chinese remainder theorem (CRT) and least squares have appeared. Recent research suggests the least squares estimator to be the most accurate in many cases. The accuracy of all of these range estimators depends upon the wavelengths chosen. This leads to the problem of selecting wavelengths that maximize accuracy. Procedures for selecting wavelengths for the beat wavelength and excess fractions methods have previously been described, but procedures for the CRT and least squares estimators are yet to be developed. In this paper, we develop an algorithm to automatically select wavelengths for use with the least square range estimator. The algorithm minimizes an optimization criterion connected with the mean square error. Interesting properties of a particular class of lattices simplify the criterion allowing minimization by depth first search. Monte-Carlo simulations indicate that wavelengths that minimize the criterion can result in considerably more accurate range estimates than wavelengths selected by ad hoc means. Refereed/Peer-reviewed

We consider the problem of distance, or range, estimation by measuring the phase of a sinusoidal signal transmitted between two locations. The distance can only be unambiguously measured if it is contained in an interval of length less than the wavelength of the signal. To increase the length of this interval, multiple phase measurements at different wavelengths can be used. The identifiable range is then extended to an interval of length equal to the least common multiple of the wavelengths. Phase measurements are noisy in practice and the problem of estimating range from multiple noisy phase measurements is non trivial. Existing solutions are based on least squares, the method of excess fractions, and on noise resilient versions of the Chinese remainder theorem (CRT). These estimators all, either explicitly, or implicitly, make an estimate of so called wrapping variables related to the whole number of wavelengths that occur over the range. In this paper, we discover an upper bound such that if all absolute phase measurement errors are less than this bound, then the least squares range estimator is guaranteed to correctly estimate the wrapping variables. We compare this with a similar bound discovered for estimators based on the CRT. The bound for the least squares estimator is often larger. This corroborates with existing empirical evidence suggesting that the least squares estimator is often more accurate. Refereed/Peer-reviewed

In MIMO-OFDM communications over channels subject to co-channel interference, beamforming (BF) is conventionally applied independently to all subcarriers. Whilst this approach maximises mutual information, it is highly computationally complex. Symbol-wise BF considerably reduces the complexity by carrying out BF in the time domain. In this paper, we generalise symbol-wise BF to take co-channel interference into account. Maximising the mutual information is infeasible in this case and instead, we propose a novel iterative algorithm that maximises the SINR before OFDM demodulation. Computer simulations show that the performance loss relative to subcarrierwise BF reduces with decreasing frequency selectivity or increasing spatial correlation. Refereed/Peer-reviewed

This paper focuses on the practical challenge of adaptation control for speech separation systems. Adaptive beamforming methods, such as minimum variance distortionless response (MDVR), can effectively extract the desired speech signal from interference and noise. However, to avoid the signal cancellation problem, the beamformer adaptation is halted when the desired speaker is active. An automated scheme for this adaptation requires classifying speakers' voice activity status, which remains a challenge for multi-speaker environments. In this paper, we propose a novel approach to identify voice activities for two speakers based on a new metric, called the beamformer-output-ratio (BOR). Statistical properties of the BOR are studied and used to develop a hypothesis-based method for voice activity classification. The method is further refined using an algorithm detecting incorrect beamformer adaptation by analysing changes in the output power of a blind adapting MVDR beamformer. Based on the new methods, we construct an automatic adaptive beamforming system to simultaneously separate speech for two speakers. The speech separation module of the system uses MVDR beamformers whose adaptation is guided by the voice activity classification. Our methods can lead to, in some cases, 20% reduction in voice activity classification error, and 8dB improvement on the output SINR. The results are verified on both synthesised signals and realistic recordings. HighlightsWe design an automated adaptive beamforming system to extract speech of two speakers.The quantity BOR and its roles in active speaker identification are introduced.The BOR-VAC method is developed, in both generic form and practical realisation.We model the beamformer output power behaviour to detect incorrect adaptation.The proposed systems are tested in both real and synthesised recordings.

Stochastic routing offers a promising substitute to deterministic routing in wireless sensor networks, mainly due to its randomized nature. Still, most of the stochastic routing algorithms are heuristic, while the optimality for a given degree of randomness is difficult to find. In this paper, we propose a theoretical framework to find the optimal stochastic routing policy that maximizes the packet delivery ratio for a given degree of randomness in routing. Our model consists of directed acyclic networks with unreliable communication links. The degree of randomness is quantified by the global entropy of routing. By employing the Lagrangian approach, a simple iterative algorithm to find the optimal stochastic routing policy is proposed. This can be used as a benchmark for performance comparison of stochastic routing algorithms. Refereed/Peer-reviewed

Timely and reliable delivery of critical information is vital for military applications and disaster relief applications. Such applications rely on communications networks, which in practice operate via unreliable links. Improving the packet delivery ratio while reducing the end-to-end delay is a major challenge for stochastic routing in networks with unreliable communication links. In this paper, we propose a novel decentralized stochastic routing algorithm to improve the packet delivery ratio and endto- end delay for wireless sensor networks (WSNs) with unreliable links. We introduce an evaluation framework based on discrete time absorbing Markov chains to evaluate the packet delivery ratio and end-to-end delay. Simulation results show that our proposed routing algorithm performs significantly better in terms of packet delivery ratio and end-to-end delay when compared to existing decentralized methods. Refereed/Peer-reviewed

We consider least squares estimators of carrier phase and amplitude from a noisy communications signal. We focus on signaling constellations that have symbols evenly distributed on the complex unit circle, i.e., M-ary phase shift keying. We show, under reasonably mild conditions on the distribution of the noise, that the least squares estimator of carrier phase is strongly consistent and asymptotically normally distributed. However, the amplitude estimator is not consistent, but converges to a positive real number that is a function of the true carrier amplitude, the noise distribution and the size of the constellation. The results of Monte Carlo simulations are provided and these corroborate the theoretical results. Refereed/Peer-reviewed

In a multi-speaker environment, voice activity classification (VAC) attempts to identify active speaker(s) at different recording periods. Using a beamformer-output-ratio (BOR) from a multi-beamforming system, an efficient solution for VAC is available by comparing the calculated BOR with pre-specified thresholds. Considering two speakers, this paper derives theoretical results on BOR statistics, including the probability distribution function and the cumulative distribution function (c.d.f.) of the BOR employing an assumption that the narrow-band signal power in the frequency domain is Gamma distributed. Using the c.d.f. of the BOR, the thresholds for VAC can be automatically calculated via a closed form expression for given acceptable misdetection rates. The method is tested with simulated recording setups for a non-reverberant environment and a 0.3 second reverberation time environment. Both simulations show high accuracy for the classification. Refereed/Peer-reviewed

The use of discrete Hartley transform (DHT) precoding was recently shown to achieve peak to average power (PAPR) reduction for OFDM. In this paper, we show that DHT precoding also achieves full diversity. We consider the sparse matrix formed by the combination of DHT and the discrete Fourier transform (DFT) and propose a receiver configuration that minimizes complexity. Furthermore, we present a detailed account of the system complexity to show that it is slightly more than uncoded conventional OFDM. Also, since this system saves the complexity required for achieving diversity gain and reducing the peak to average power (PAPR), it reduces the system complexity when the PAPR reduction and diversity techniques are taken into account for conventional OFDM. We analytically show that this system achieves full diversity and then verify it using simulation results. Simulations results also show that the system has a substantial improvement in bit error performance over conventional OFDM. Refereed/Peer-reviewed

Improving convergence rate is one of the major challenges in stochastic routing for wireless sensor networks. Randomized approach of node selection results in a higher convergence time which is not desirable for delay-sensitive applications. In [4], we proposed a novel routing algorithm that performs better than the existing methods in terms of the convergence rate. In this paper, we analyze the basic concept behind our proposed routing algorithm, improving the rate of routing out of the neighborhood for any given node, which will improve the convergence rate. Furthermore, we derive bounds for transition probabilities which will improve the convergence rate with reference to the random walking strategy and formulate a closed-form expression for optimal transition probability selection. Refereed/Peer-reviewed

In a conversation between multiple speakers, each person participates in the speech at different times. Therefore the active speakers in each speech segment are unknown. However, identifying the voice activity (VA) of the speakers of interest is required for adaptive beamforming techniques such as minimum variance distortionless response beamforming and the adaptive blocking beamforming (AB). Considering two speakers, this paper addresses a voice activity classification (VAC) problem that focuses on identifying the active speaker(s) in each speech segment. The proposed method is based on a new concept, the beamformer-output-ratio (BOR). This value is calculated from the outputs of two different beamformers steering at two speakers. The first part of the paper introduces the definition of BOR, the VAC method using BOR and simulation results. The simulations are based on real recordings and show a high classification accuracy. In the second part of the paper, the theoretical results of the BOR of the delay-and-sum (DS) beamforming are presented, including BOR formula derived in different environments and its behaviour in relation to parameter errors. Refereed/Peer-reviewed

Improving the packet transmission delay is one of the major challenges of stochastic routing in wireless sensor networks: the use of random paths from source to destination nodes results in longer routes on average, which is not desirable in delay-sensitive applications. In this paper, we propose a novel distributed and decentralized stochastic routing algorithm to minimize the average packet transmission delay of the network. We also provide an analytical expression for the average packet transmission delay for a circular network using a discrete time Markov chain model and we discuss the performance improvement with respect to random walking methods. Simulation results demonstrate that our proposed routing method significantly improves the average packet transmission delay when compared to existing methods and provides a near optimal solution. Refereed/Peer-reviewed

In this paper, we investigate the load balancing effect of stochastic routing in wireless sensor networks. Our motivation is based on the common claim that the randomness in routing achieves energy-efficient load balancing. We introduce an evaluation framework based on discrete time absorbing Markov chains for destination-based stochastic routing. Based on this stochastic routing framework, we investigate the load balancing effect on undirected and directed networks with randomly positioned nodes. Simulation results demonstrate that stochastic routing does not necessarily achieve energy-efficient load balancing in undirected networks. Furthermore, we analyze the performance of our distributed and decentralized stochastic routing algorithm, namely expander routing method. Simulation results shows that our expander routing method performs significantly better in terms of packet transmission delay while achieving energyefficient load balancing in directed networks. Refereed/Peer-reviewed

Recently, a T-transform based multicarrier communication system with significant uncoded BER performance improvement over conventional OFDM in a Rayleigh fading channel was proposed. However, due to the involvement of Walsh Hadamard transform (WHT), the T-transform OFDM system does not satisfy the cyclic convolution property and hence fails to diagonalize the channel matrix, resulting in an enormous equalization complexity. In this paper, we propose a new receiver processing mechanism where the T-transform is replaced by two equivalent transforms and the equalization is carried out in between them. The new approach diagonalizes the channel matrix and single tap equalization is possible without any compromise in the performance. The detailed computational complexity of the proposed approach is also presented and compared with some other schemes. Refereed/Peer-reviewed

In this paper, we propose a novel algorithm for distributed and decentralized stochastic routing to optimize the convergence rate and the resilience of routing. More precisely, the novelty of our method is the provision of a stochastic routing technique which greatly improves the spectral gap of the routing matrix, as compared to existing methods. We define a novel measure of effective expansion capability of a node, which we use to maximize the spectral gap of the stochastic routing matrix. Simulation results demonstrate that our proposed routing method significantly improves the convergence rate and resilience of routing compared to other existing methods. Refereed/Peer-reviewed

A major challenge in wireless sensor networks(WSN) is that spatially distributed nodes need to achieve a globaltask in a completely decentralised manner. Motivated by the factthat optimisation problems in WSNs can often be formulatedas Markov random field (MRF) energy minimisation, a generalMRF-based framework for the design of distributed WSN algorithmswas proposed recently. Building upon this frameworkand the theory of dual decomposition, we develop a novel WSNoptimisation algorithm that is applicable to a wide variety of networkproblems such as routing and power control. Our algorithmis completely distributed and is characterised by simple, deterministicand identical per-node processing. Routing of controlinformation through the network is avoided as nodes exclusivelyprocess information from their local neighbourhoods. We applyour algorithm to a multiple access resource allocation problemand demonstrate rapid convergence to the global optimum. Refereed/Peer-reviewed

In communication systems that use orthogonal frequency-division multiplexing and multiple transmit and receive antennas, beamforming (BF) is conventionally carried out on a subcarrier basis. The computational requirements are high as dedicated discrete Fourier transform (DFT) processors are needed for each antenna. Considerable complexity reductions can be achieved by symbol-wise BF, which performs the transmit and receive BF operations in the time domain, and therefore requires only one DFT processor per terminal. In this paper, we investigate symbol-wise BF for the mitigation of co-channel interference on spatially correlated channels, which are modelled with the Kronecker model. We show analytically that symbolwise BF is the optimal BF scheme when the channel is frequency-flat or fully correlated, and present a novel iterative algorithm for the computation of the optimal antenna weights. Monte-Carlo simulations confirm that the relative performance loss of symbolwise BF becomes negligible when approaching full correlation.

OFDM is well suited to indoor wireless communication systems that suffer from multipath delay spread. However very high rate systems may impose severe computational demands in both the modem and codec. This paper considers analog filter requirements and the effects of timing drift in Gbit Wireless LAN systems using OFDM. Due to the high data rates we assume one sample per time-domain symbol at the transmitter and receiver. This baud-rate constraint requires more careful design of the transmit and receive filters than normally needed in oversampled OFDM designs. Achieving high-order filter responses at these bandwidths is not straightforward. The paper considers the interaction of timing drift with imperfect analog filters and describes a method to optimise performance under various OFDM scenarios. Results are presented to quantify the impact of non-ideal reconstruction and anti-alias filters on system capacity for a range of filter orders and types.

High speed frequency dividers are critical parts of frequency synthesisers in wireless systems. These dividers allow the output frequency from a voltage controlled oscillator to be compared with a much lower external reference frequency that is commonly used in these synthesisers. Common trade-offs in high frequency dividers are speed of division, power consumption, real estate area, and output signal dynamic range. In this paper we demonstrate the design of a high frequency, low power divider in 0.18 µm SiGe BiCMOS technology. Three dividers are presented, which are a regenerative divider, a master-slave divider, and a combination of regenerative and master-slave dividers to perform a divide-by-8 chain. The dividers are used as part of a 60 GHz frequency synthesizer. The simulation results are in agreement with measured performance of the regenerative divider. At 48 GHz the divider consumes 18 mW from a 1.8 V supply voltage. The master-slave divider operates up to 36 GHz from a very low supply voltage, 1.8 V. The divide-by-8 operates successfully from 40 GHz to 50 GHz.