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Peter J. Smith

Publications and source records attributed to Peter J. Smith.

At least 37 records · Page 2Linked to original sources

Second Order Channel Statistics: An Analysis for Optimal Single-user RIS Systems

A key challenge facing reconfigurable intelligent surfaces (RISs) is channel state information acquisition. Passive RISs cannot generate pilot signals or process data, making rapid temporal changes in the channel problematic. Additionally, the impact of spatial changes in RIS channels has not been thoroughly investigated. Therefore, in this work, we use second order statistics to investigate the spatio-temporal behaviour of a single-user (SU) RIS system. Assuming a line-of-sight (LoS) RIS to base station (BS) link, we derive an exact expression for the level crossing rate (LCR) of the RIS link (user equipment (UE)-RIS-BS path) and propose a numerically stable approximation for the LCR of the global UE-BS channel. Each LCR expression attained is then utilised to find the corresponding average fade duration (AFD). The temporal signal-to-noise ratio (SNR) correlation is also derived assuming an LoS RIS-BS link. Assuming a Ricean RIS-BS link, expressions for the spatial correlation matrix of the global channel and the mean SNR loss due to channel ageing are derived. All of the analyses are verified by simulation, and the impact of key system parameters is investigated. We show that the use of an RIS does not significantly amplify changes in the channel.

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High SNR Probabilities of Continuous Fluid Antenna Systems in Ricean Environments

We consider a single-user (SU) continuous fluid antenna system (CFAS) employing matched filtering (MF) operating over a Ricean fading channel. Focusing on the upper tail of the received signal-to-noise ratio (SNR) distribution (the high SNR probability (HSP)), we derive accurate approximations for the HSP in 1, 2, and 3 dimensions using the expected Euler characteristic (EEC), presenting the first analytical results for a CFAS in a Ricean environment. In the process, we provide the first closed-form expression for the Euler characteristic density of a non-central chi-squared random field. We then examine the impact of the Ricean K-factor on the CFAS performance, emphasizing the critical role of channel variations in achieving a strong HSP.

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Performance Characterization of Continuous Reconfigurable Intelligent Surfaces

We consider a reconfigurable intelligent surface (RIS) that can implement a phase rotation continuously over the whole surface rather than via a finite number of discrete elements. Such an RIS can be considered a design for future systems where advances in metamaterials make such an implementation feasible or as the limiting case where the number of elements in a traditional RIS increases in a given area. We derive the optimal RIS design for the single-user (SU) scenario assuming a line-of-sight (LoS) from the RIS to the base station (BS) and correlated Rayleigh fading for the other links. We also derive the associated optimal signal-to-noise ratio (SNR) and its mean, a bound on the mean spectral efficiency (SE), an approximation to the SNR outage probability and an approximation to the coefficient of variation for the investigation of channel hardening.

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Rician Channel Modelling for Super Wideband MIMO Communications

Recent developments in Multiple-Input-Multiple-Output (MIMO) technology include packing a large number of antenna elements in a compact array to access the bandwidth benefits provided by higher mutual coupling (MC). The resulting super-wideband (SW) systems require a circuit-theoretic framework to handle the MC and channel models which span extremely large bands. Hence, in this paper, we make two key contributions. First, we develop a physically-consistent Rician channel model for use with SW systems. Secondly, we express the circuit-theoretic models in terms of a standard MIMO model, so that insights into the effects of antenna layouts, MC, and bandwidth can be made using standard communication theory. For example, we show the bandwidth widening resulting from the new channel model. In addition, we show that MC distorts line-of-sight paths which has beamforming implications. We also highlight the interaction between spatial correlation and MC and show that tight coupling reduces spatial correlations at low frequencies.

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Probing populations of dark stellar remnants in the globular clusters 47 Tuc and Terzan 5 using pulsar timing

We present a new method to combine multimass equilibrium dynamical models and pulsar timing data to constrain the mass distribution and remnant populations of Milky Way globular clusters (GCs). We first apply this method to 47 Tuc, a cluster for which there exists an abundance of stellar kinematic data and which is also host to a large population of millisecond pulsars. We demonstrate that the pulsar timing data allow us to place strong constraints on the overall mass distribution and remnant populations even without fitting on stellar kinematics. Our models favor a small population of stellar-mass BHs in this cluster (with a total mass of $446^{+75}_{-72} \mathrm{M_\odot}$), arguing against the need for a large ($ > 2000 \ \mathrm{M_\odot}$) central intermediate-mass black hole. We then apply the method to Terzan 5, a heavily obscured bulge cluster which hosts the largest population of millisecond pulsars of any Milky Way GC and for which the collection of conventional stellar kinematic data is very limited. We improve existing constraints on the mass distribution and structural parameters of this cluster and place stringent constraints on its black hole content, finding an upper limit on the mass in BHs of $\sim 4000 \ \mathrm{M_\odot}$. This method allows us to probe the central dynamics of GCs even in the absence of stellar kinematic data and can be easily applied to other GCs with pulsar timing data, for which datasets will continue to grow with the next generation of radio telescopes.

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Multimass modelling of Milky Way globular clusters -- II. present-day black hole populations

Populations of stellar-mass black holes (BHs) in globular clusters (GCs) influence their dynamical evolution and have important implications on one of the main formation channels for gravitational wave sources. Inferring the size of these populations remains difficult, however. In this work, multimass models of 34 Milky Way GCs, first presented in Dickson et al., are used to explore the present-day BH populations. Direct constraints on both the total and visible mass components provided by several observables allow these models to accurately determine the distribution of the dark mass (including BHs) within clusters, as we demonstrate in a proof-of-concept fitting of the models to mock observations extracted from Monte Carlo cluster models. New constraints on the BH population retained to the present-day in each cluster are inferred from our models. We find that BH mass fractions ranging from 0 to 1 per cent of the total mass are typically required to explain the observations, except for Omega Cen, for which we infer a mass fraction above 5 per cent, in agreement with previous works. Relationships between the dark remnant populations and other cluster parameters are examined, demonstrating a clear anti-correlation between the amount of BHs and mass segregation between visible stars, as well as a correlation between remnant mass fractions and the dynamical age of clusters. Our inferred BH populations are in good agreement overall with other recent studies using different methodologies, but with notable discrepancies for individual clusters.

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Protecting Massive MIMO-Radar Coexistence: Precoding Design and Power Control

This paper studies the coexistence between a downlink multiuser massive multi-input-multi-output (MIMO) communication system and MIMO radar. The performance of the massive MIMO system with maximum ratio ($\MR$), zero-forcing ($\ZF$), and protective $\ZF$ ($\PZF$) precoding designs is characterized in terms of spectral efficiency (SE) and by taking the channel estimation errors and power control into account. The idea of $\PZF$ precoding relies on the projection of the information-bearing signal onto the null space of the radar channel to protect the radar against communication signals. We further derive closed-form expressions for the detection probability of the radar system for the considered precoding designs. By leveraging the closed-form expressions for the SE and detection probability, we formulate a power control problem at the radar and base station (BS) to maximize the detection probability while satisfying the per-user SE requirements. This optimization problem can be efficiently tackled via the bisection method by solving a linear feasibility problem. Our analysis and simulations show that the $\PZF$ design has the highest detection probability performance among all designs, with intermediate SE performance compared to the other two designs. Moreover, by optimally selecting the power control coefficients at the BS and radar, the detection probability improves significantly.

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Continuous Fluid Antenna Systems: Modeling and Analysis

Fluid antennas (FAs) is a promising technology for introducing flexibility and reconfigurability in wireless networks. Recent research efforts have highlighted the potential gains that can be achieved in comparison to conventional antennas. These works assume that the FA has a discrete number of positions that the liquid can take. However, from a practical standpoint, the liquid moves in a continuous fashion to any point inside the FA. In this paper, we focus on a continuous FA system (CFAS) and present a general framework for its design and analytical evaluation. In particular, we derive closed-form analytical expressions for the level crossing rate (LCR) and the average fade duration of the continuous signal-to-interference ratio (SIR) process over the FA's length. Then, by leveraging the LCR expression, we characterize the system's outage performance with a bound on the cumulative distribution function of the SIR's supremum. Our results confirm that the CFAS outperforms its discrete counterpart and thus provides the performance limits of FA-based systems.

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Optimal Phase Design for RIS Channel Estimation

We develop an optimal version of a prior two-stage channel estimation protocol for RIS-assisted channels. The new design uses a modified DFT matrix (MDFT) for the training phases at the RIS and is shown to minimize the total channel estimation error variance. In conjunction with interpolation (estimating fewer RIS channels), the MDFT approach accelerates channel estimation even when the channel from base station to RIS is line-of-sight. In contrast, prior two-stage techniques required a full-rank channel for efficient estimation. We investigate the resulting channel estimation errors by comparing different training phase designs for a variety of propagation conditions using a ray-based channel model. To examine the overall performance, we simulate the spectral efficiency with MRC processing for a single-user RIS-assisted system using an existing optimal design for the RIS transmission phases. Results verify the optimality of MDFT while simulations and analysis show that the performance is more dependent on the user-to-RIS channel correlation and the coarseness of the interpolation used, rather than the training phase design. For example, under a scenario with more highly correlated channels, the procedure accelerates channel estimation by a factor of 16, while the improvement is a factor of 5 in a less correlated case. The overall procedure is extremely robust, with a maximum performance loss of 1.5bits/sec/Hz compared to that with perfect channel state information for the considered channel conditions.

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Phase Dependent Loss Analysis for RIS Systems

In this paper we focus on phase dependent loss (PDL), an important aspect of reconfigurable intelligent surfaces (RIS) where the signals reflected from the RIS elements are attenuated by varying amounts depending on the phase rotation provided by the element. To evaluate the effects of PDL, we analyse the SNR of a SIMO RIS-aided wireless link. We assume that the channel between the base station (BS) and RIS is a rank-1 LOS channel while the user (UE)-BS and UE-RIS are correlated Rayleigh channels. The RIS design is optimal in the absence of PDL and maximizes the SNR in this scenario. Specifically, we derive a closed form expression for the mean SNR in the presence of PDL. The attenuation function used for PDL was developed from a detailed circuit analysis of RIS elements. Leveraging the derived results, we analytically characterise the impact of PDL on the mean SNR. Numerical results are conducted to validate the derived expressions and verify the analysis.

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Efficient Optimization Techniques for RIS-aided Wireless Systems

The objective of this paper is to develop simple techniques to enhance the performance of multi-user RIS aided wireless systems. Specifically, we develop a novel technique called \textit{channel separation} which provides a better understanding of how the RIS phases affect the uplink sum rate and sum rates for ZF and MMSE linear receivers. Leveraging channel separation, we propose a simple iterative algorithm to improve the uplink sum rate and the sum rates of ZF and MMSE linear receivers when discrete RIS phases are considered. For continuous RIS phases, we derive simple closed form solutions to enhance the uplink sum rate and reduce the total mean square error of the MMSE combiner. The latter metric is a tractable alternative to maximizing sum rates for ZF and MMSE. Numerical simulations are performed for all optimization techniques and the effectiveness of each technique is compared to a full numerical optimization procedure, namely an interior point (IP) algorithm.

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Optimal SNR Analysis for Single-user RIS Systems in Ricean and Rayleigh Environments

We present an analysis of the optimal uplink (UL) SNR of a SIMO Reconfigurable Intelligent Surface (RIS)-aided wireless link. We assume that the channel between base station (BS) and RIS is a rank-1 LOS channel while the user (UE)-RIS and UE-BS channels are correlated Ricean. For the optimal RIS matrix, we derive an exact closed form expression for the mean SNR and an approximation for the SNR variance leading to an accurate gamma approximation to the distribution of the UL SNR. Furthermore, we analytically characterise the effects of correlation and the Ricean K-factor on SNR, showing that increasing the K-factor and correlation in the UE-BS channel can have negative effects on the mean SNR, while increasing the K-factor and correlation in the UE-RIS channel improves system performance. We also present favourable and unfavourable channel scenarios which provide insight into the sort of environments that improve or degrade the mean SNR. We also show that the relative gain in the mean SNR when transitioning from an unfavourable to a favourable environment saturates to $(4-π)/π$ as $N \rightarrow \infty $

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Tight Bounds on the Optimal UL Sum-Rate of MU RIS-aided Wireless Systems

The objective of this paper is to develop simple techniques to bound the optimal uplink sum-rate of multi-user RIS-aided wireless systems. Specifically, we develop a novel technique called \textit{channel separation} which provides a new understanding as to how the RIS phases affect the sum-rate. Leveraging channel separation, we derive upper and lower bounds on the optimal sum-rate. In addition, we propose a low-complexity alternating optimization algorithm to obtain near-optimal sum-rate results. Numerical results demonstrate the tightness of the bounds and show that the alternating optimization approach delivers sum-rate values similar to the results of a full numerical optimization procedure. Furthermore, in practical scenarios where hardware limitations cause the RIS phases to be quantized, our lower bound can still be applied and shows that the sum-rate is robust to quantization, even with low resolution.

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Optimal SNR Analysis for Single-user RIS Systems

In this paper, we present an analysis of the optimal uplink SNR of a SIMO Reconfigurable Intelligent Surface (RIS)-aided wireless link. We assume that the channel between base station and RIS is a rank-1 LOS channel while the user (UE)-RIS and UE-base station (BS) channels are correlated Rayleigh. We derive an exact closed form expression for the mean SNR and an approximation for the SNR variance leading to an accurate gamma approximation to the distribution of the UL SNR. Furthermore, we analytically characterise the effects of correlation on SNR, showing that correlation in the UE-BS channel can have negative effects on the mean SNR, while correlation in the UE-RIS channel improves system performance. For systems with a large number of RIS elements, correlation in the UE-RIS channel can cause an increase in the mean SNR of up to 27.32% relative to an uncorrelated channel.

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Space-Constrained Arrays for Massive MIMO

We analyse the behaviour of a massive multi-user MIMO (MU-MIMO) system comprising a base station (BS) equipped with one of five different antenna topologies for which the spatial aperture is either unconstrained, or space-constrained. We derive the normalized mean interference (NMI) with a ray-based channel model, as a metric for topology comparison in each of the two cases. Based on the derivation for a horizontal uniform rectangular array (HURA) in [1], we provide closed-form NMI equations for the uniform linear array (ULA) and uniform circular array (UCirA). We then derive the same for a vertical URA (VURA) and uniform cylindrical array (UCylA). Results for the commonly-considered unconstrained case confirm the prior understanding that topologies with wider azimuth footprints aid performance. However, in the space-constrained case performance is dictated by the angular resolution afforded by the topology, particularly in elevation. We confirm the behavioural patterns predicted by the NMI by observing the same patterns in the system SINR with minimum mean-squared error (MMSE) processing.

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3D Mobility Models and Analysis for UAVs

We present a flexible family of 3D mobility models suitable for unmanned aerial vehicles (UAV). Based on stochastic differential equations, the models offer a unique property of explicitly incorporating the mobility control mechanism and environmental perturbation, while enabling tractable steady state solutions for properties such as position and connectivity. Specifically, motivated by UAV flight data, for a symmetric mobility model with an arbitrary control mechanism, we derive the steady state distribution of the distance from the target position. We provide closed form expressions for the special cases of the Ornstein-Uhlenbeck (OU) process and on-off control (OC). We extend the model to incorporate imperfect positioning and asymmetric control. For a practically relevant scenario of partial symmetry (such as in the x-y plane), we present steady state position results for the OU control. Building on these results, we derive UAV connectivity probability results based on a SNR criterion in a Rayleigh fading environment.

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Favorable Propagation with User Cluster Sharing

We examine the favorable propagation (FP) behavior of a massive multi-user multiple-input-multiple-output (MU-MIMO) system equipped with a uniform linear array (ULA), horizontal uniform rectangular array (HURA) or uniform circular array (UCA) using a ray-based channel model with user cluster sharing. We demonstrate FP for these systems and provide analytical expressions for the mean-squared distance (MSD) of the FP metric from its large-system limit for each of the aforementioned topologies. We use these results to examine the detrimental effects of user cluster sharing on FP behavior, and demonstrate the superior performance of the ULA as compared to the UCA and the HURA with equal inter-element spacing. Although cluster sharing has a negative impact on FP for finite arrays, we additionally examine the asymptotic rate of convergence to FP as a function of array size and show that this rate is unchanged with or without user cluster sharing.

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Channel Correlation Diversity in MU-MIMO Systems -- Analysis and Measurements

In multiuser multiple-input multiple-output (MU-MIMO) systems, channel correlation is detrimental to system performance. We demonstrate that widely used, yet overly simplified, correlation models that generate identical correlation profiles for each terminal tend to severely underestimate the system performance. In sharp contrast, more physically motivated models that capture variations in the power angular spectra across multiple terminals, generate diverse correlation patterns. This has a significant impact on the system performance. Assuming correlated Rayleigh fading and downlink zero-forcing precoding, tight closed-form approximations for the average signal-to-noise-ratio, and ergodic sum spectral efficiency are derived. Our expressions provide clear insights into the impact of diverse correlation patterns on the above performance metrics. Unlike previous works, the correlation models are parameterized with measured data from a recent 2.53 GHz urban macrocellular campaign in Cologne, Germany. Overall, results from this paper can be treated as a timely re-calibration of performance expectations from practical MU-MIMO systems.

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