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Emad Alsusa

Publications and source records attributed to Emad Alsusa.

At least 19 recordsLinked to original sources

Cooperative LEO-Terrestrial Multistatic ISAC: CRLB Analysis, Scaling Laws, and Satellite Selection

Low Earth orbit (LEO) satellites provide elevated and spatially diverse viewpoints for enhancing three-dimensional (3-D) sensing in integrated satellite-terrestrial networks (ISTNs). This paper investigates a LEO-assisted terrestrial multistatic integrated sensing and communication (ISAC) network for 3-D target localisation, where multiple LEO satellites act as cooperative sensing illuminators and provide additional bistatic observations to distributed terrestrial radar receivers. We first model cooperative satellites as a homogeneous Poisson point process (PPP) and derive a tractable approximation of the average hybrid Cramér-Rao lower bound (CRLB). The resulting scaling laws show that the root-CRLB decreases with the inverse square root of the mean number of cooperative satellites for a fixed cooperation region, while increasing the cooperation radius at fixed satellite density yields logarithmic diminishing returns. We then develop an Earth-curvature-aware Walker model incorporating orbital structure, satellite motion, visibility, and time-varying sensing geometry, and derive a tractable approximation of the corresponding hybrid CRLB. Analytical bounds on the marginal gain and a sufficient condition for ordering candidate satellites are obtained. Based on these results, a CRLB-oriented greedy satellite-selection strategy is proposed to account for SCNR-dependent reliability and geometric complementarity with the terrestrial sensing configuration. The proposed strategy consistently outperforms benchmarks and approaches exhaustive-search performance with substantially lower complexity. Monte Carlo simulations validate the analytical approximations for both models.

eess.SP

A Unified KLD Framework for Duplexity and Deployment Paradigms in Cell-Free mMIMO-ISAC

This paper presents a comparative study of four potential operating configurations for distributed cell-free massive multiple-input multiple-output (CF-mMIMO) ISAC, spanning separated (SE) and shared (SH) access point (AP) deployment with half-duplex (HD) and full-duplex (FD) paradigms. The system comprises distributed APs serving multiple downlink (DL) and uplink (UL) users while simultaneously detecting radar targets. The configurations incorporate realistic impairments at the AP receivers: residual self-interference (SI) from transmit--receive leakage under FD operation, imperfect interference cancellation (IC) of the known radar and DL waveforms due to channel-estimation errors, and environmental clutter. To establish a common analytical scale for communication and sensing, the Kullback--Leibler divergence (KLD) is adopted as a unifying measure that represents both subsystems in comparable quantities, thereby enabling consistent comparison between error-rate and detection metrics. A generalised likelihood ratio test (GLRT) framework is developed, yielding closed-form expressions that link the KLD to the detection probability. Our results confirm the derived KLD-to-symbol error rate (SER) and KLD-to-detection links: with adequate SI suppression and IC quality, FD attains substantial communication gains over HD while preserving strong radar detection, and SH deployment raises both communication and radar performance through its larger effective aperture, though its radar gain then depends on cancellation quality, which SE deployment avoids by isolating the subsystems. These trends persist under imperfect channel state information (CSI) and sensing estimation, and a complexity analysis attributes the SH deployment and FD gains to a higher per-configuration processing cost, yielding deployment guidelines and quantitative design thresholds for next-generation CF-mMIMO ISAC systems.

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On the SER Performance of ZF and MMSE Receivers in Pilot-Aided Simultaneous Communication and Localization

In this paper, a symbol error rate (SER) analysis is provided to evaluate the impact of localization inaccuracy on the communication performance under Zero-Forcing (ZF) and Minimum Mean-Square Error (MMSE) equalizers. Specifically, we adopt a pilot-aided simultaneous communication and localization (PASCAL) system, in which multiple drones actively transmit signals towards the base station (BS). Upon receiving the signal, the BS estimates the drones' location parameters to reconstruct the channel matrix, which is then utilized for ZF and MMSE equalization. As the channel matrix is characterized by the estimated parameters associated with the target's location and the matrix inversion involved in ZF and MMSE further complicates the analysis, obtaining a closed-form SER expression becomes intractable. Thus, a tightly approximated SER expression is respectively derived for ZF and MMSE by using a hybrid approximation method incorporating Neumann approximation and Taylor approximation. Our analysis reveals several important design insights: first, the average SER of drone $k$ for both ZF and MMSE can be affected by the localization errors from all drones including drone $k$; second, the average SER of ZF is unaffected by the estimation inaccuracy of range, whereas the average SER of MMSE is influenced by it; third, ZF and MMSE is the most susceptible to the influence of angle estimation errors compared to the other localization errors; fourth, ZF is highly sensitive to localization errors and may be even worse than maximal ratio combining (MRC) under some conditions of significant estimation errors. Numerical simulation results verify our findings and also validate the accuracy of the analysis across a wide range of system parameters.

cs.IT

A Framework for Holistic KLD-based Waveform Design for Multi-User-Multi-Target ISAC Systems

This paper introduces a novel framework aimed at designing integrated waveforms for robust integrated sensing and communication (ISAC) systems. The system model consists of a multiple-input multiple-output (MIMO) base station that simultaneously serves communication user equipments (UEs) and detects multiple targets using a shared-antenna deployment scenario. By leveraging Kullback-Leibler divergence (KLD) to holistically characterise both communication and sensing subsystems, three optimisation problems are formulated: (i) radar waveform KLD maximisation under communication constraints, (ii) communication waveform KLD maximisation subject to radar KLD requirements, and (iii) an integrated waveform KLD-based optimisation for ISAC that jointly balances both subsystems. The first two problems are solved using a projected gradient method with adaptive penalties for the radar waveforms and a gradient-assisted interior point method (IPM) for the communication waveforms. The third, integrated waveform optimisation approach adopts an alternating direction method of multipliers (ADMM) framework to unify radar and communication waveform designs into a single integrated optimisation, thereby synergising sensing and communication objectives and achieving higher overall performance than either radar- or communication-only techniques. Unlike most existing ISAC waveform designs that regard communication signals solely as interference for sensing, the proposed framework utilises the holistic ISAC waveform-that is, the superimposed communication and sensing signals-to boost detection performance in the radar subsystem. Simulation results show significant improvements in both radar detection and communication reliability compared with conventional zero-forcing beamforming, identity-covariance radar baselines, and traditional optimisation approaches,..

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RIS-enabled Multi-user M-QAM Uplink NOMA Systems: Design, Analysis, and Optimization

Non-orthogonal multiple access (NOMA) is widely recognized for enhancing the energy and spectral efficiency through effective radio resource sharing. However, uplink NOMA systems face greater challenges than their downlink counterparts, as their bit error rate (BER) performance is hindered by an inherent error floor due to error propagation caused by imperfect successive interference cancellation (SIC). This paper investigates BER performance improvements enabled by reconfigurable intelligent surfaces (RISs) in multi-user uplink NOMA transmission. Specifically, we propose a novel RIS-assisted uplink NOMA design, where the RIS phase shifts are optimized to enhance the received signal amplitudes while mitigating the phase rotations induced by the channel. To achieve this, we first develop an accurate channel model for the effective user channels, which facilitates our BER analysis. We then introduce a channel alignment scheme for a two-user scenario, enabling efficient SIC-based detection and deriving closed-form BER expressions. We further extend the analysis to a generalized setup with an arbitrary number of users and modulation orders for quadrature amplitude modulation signaling. Using the derived BER expressions, we develop an optimized uplink NOMA power allocation (PA) scheme that minimizes the average BER while satisfying the user transmit power constraints. It will be shown that the proposed NOMA detection scheme, in conjunction with the optimized PA strategy, eliminate SIC error floors at the base station. The theoretical BER expressions are validated using simulations, which confirms the effectiveness of the proposed design in eliminating BER floors.

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Pilot-Aided Simultaneous Communication And Localisation (PASCAL) Under Practical Imperfections

This paper introduces a system model called pilot-aided simultaneous communication and localisation (PASCAL) and illustrates its performance in the presence of practical gain and phase imperfections. Specifically, we consider the scenario where multiple single-antenna unmanned aerial vehicles (UAVs) transmit data packets to a multi-antenna base station (BS) that has the dual responsibility of detecting communication signals and localising UAVs using their pilot symbols. Two forms of receiver signal processing approaches are adopted, including disjoint localisation and communication by using maximum likelihood estimation and multiple signal classification (MUSIC), as well as joint localisation and data detection achieved by the newly proposed algorithms. To evaluate the asymptotic localisation performance in the presence of gain-phase imperfections, the Cramér-Rao lower bound (CRLB) is derived, while for evaluating the communication's performance, the average sum data rate (SDR) for all the UAVs is derived in closed-form. It is shown that these derived expressions concur with simulations. The results reveal that while the proposed PASCAL system can be sensitive to gain-phase imperfections, it remains to be a powerful and efficient means to achieve reliable simultaneous localisation and communications.

cs.IT

On the Achievable Error Rate Performance of Pilot-Aided Simultaneous Communication and Localisation

This paper investigates the symbol error rate (SER) performance of the pilot-aided simultaneous communication and localisation (PASCAL) system. A scenario where multiple drones transmit communication signals to a base station (BS), which needs to simultaneously decode the signals and continuously locate the drones' positions during the communication session, is considered. The BS operates in two stages: first, it estimates the drones' location parameters using pilot signals; second, it performs data detection by reconstructing the channel response based on the estimated location parameters. The theoretical analysis presented demonstrates that the estimated location parameters follow Gaussian distributions with means equal to the actual values and variances determined by the root mean square error (RMSE) of the estimator. Using these distributions, the average SER is derived to quantify the impact of localisation errors on decoding performance. This analysis highlights the synergy between communication and localisation, providing valuable insights into the influence of localisation inaccuracies on the performance of location-aware communication systems. Simulations are conducted to validate the theoretical derivations.

cs.IT

Performance Analysis of Pair-wise Symbol Detection in Uplink NOMA-ISaC Systems

This paper investigates the bit error rate (BER) and outage probability performance of integrated sensing and communication (ISaC) in uplink non-orthogonal multiple access (NOMA) based Internet of Things (IoT) systems. Specifically, we consider an ISaC system where the radar signal is designed to be orthogonal to the communication signal over two symbol periods so that its interference on the communication signal is completely eliminated when detecting the data in pairs of consecutive symbols. This is akin to multi-symbol rate NOMA systems except in this case as the radar bears no data, its waveform is manipulated to be orthogonal to the transmitted communication signal. To eliminate potential decision ambiguity during the pair-wise data detection, a constant phase-offset between adjacent communication symbols is applied at the transmitter. The performance of such a system is analyzed through deriving analytical expressions for the exact BER of zero-forcing (ZF) based receivers. In addition, close-form expressions for the upper BER bound and the outage probability for both ZF and the joint maximum likelihood (JML) receivers are presented. The results show that the derived expressions are perfectly matched with the simulation results. The obtained expressions provide an insight into the performance of this novel ISaC system including demonstrating the impact of various parameters and showing how the ZF receiver provides a useful trade-off between performance and complexity relative to the JML receiver.

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Novel Many-to-Many NOMA-based Communication Protocols for Vehicular Platoons

Non-orthogonal multiple access (NOMA) is a promising technique for ultra-reliable low-latency communication as it provides higher spectral efficiency and lower latency. In this work, we propose novel many-to-many (M2M) NOMA-based schemes to exchange broadcast, multicast, and unicast messages between cluster heads (CHs) of vehicular platoons. Specifically, we design uplink-M2M-NOMA (UM-NOMA), downlink-M2M-NOMA (DM-NOMA) and joint uplink-downlink-M2M-NOMA (UDM-NOMA) schemes for peer-to-peer vehicular ad hoc networks (VANETs). We propose a unique clustering design for full-duplex communication that utilizes the high throughput millimeter-wave (mmWave) channels. Furthermore, we investigate jointly optimal CH selection (CHS) and power allocation (PA) to maximize the network sum rate and devise a computationally efficient tailored-greedy algorithm that yields near-optimal performance. We also propose a super-cluster formation protocol to further limit the overhead of successive interference cancellation (SIC). The results reveal that in most of the considered scenarios, the proposed UDM-NOMA scheme outperforms orthogonal multiple access (OMA) in terms of sum rate by up to 50% even when the SIC receiver errors reach 10%.

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Optimization of Energy-Constrained IRS-NOMA Using a Complex Circle Manifold Approach

This work investigates the performance of intelligent reflective surfaces (IRSs) assisted uplink non-orthogonal multiple access (NOMA) in energy-constrained networks. Specifically, we formulate and solve two optimization problems; the first aims at minimizing the sum of users' transmit power, while the second targets maximizing the system level energy efficiency (EE). The two problems are solved by jointly optimizing the users' transmit powers and the beamforming coefficients at IRS subject to the users' individual uplink rate and transmit power constraints. A novel and low complexity algorithm is developed to optimize the IRS beamforming coefficients by optimizing the objective function over a \textit{complex circle manifold} (CCM). To efficiently optimize the IRS phase shifts over the manifold, the optimization problem is reformulated into a feasibility expansion problem which is reduced to a max-min signal-plus-interference-ratio (SINR). Then, with the aid of a smoothing technique, the exact penalty method is applied to transform the problem from constrained to unconstrained. The proposed solution is compared against three semi-definite programming (SDP)-based benchmarks which are semi-definite relaxation (SDR), SDP-difference of convex (SDP-DC) and sequential rank-one constraint relaxation (SROCR). The results show that the manifold algorithm provides better performance than the SDP-based benchmarks, and at a much lower computational complexity for both the transmit power minimization and EE maximization problems. The results also reveal that IRS-NOMA is only superior to orthogonal multiple access (OMA) when the users' target achievable rate requirements are relatively high.

cs.IT

Generalized BER Performance Analysis for SIC-based Uplink NOMA Systems

Non-orthogonal multiple access (NOMA) is widely recognized for its spectral and energy efficiency, which allows more users to share the network resources more effectively. This paper provides a generalized bit error rate (BER) performance analysis of successive interference cancellation (SIC)-based uplink NOMA systems under Rayleigh fading channels, taking into account error propagation resulting from SIC imperfections. Exact closed-form BER expressions are initially derived for scenarios with 2 and 3 users using quadrature phase shift keying (QPSK) modulation. These expressions are then generalized to encompass any arbitrary rectangular/square M-ary quadrature amplitude modulation (M-QAM) order, number of NOMA users, and number of BS antennas. Additionally, by utilizing the derived closed-form BER expressions, a simple and practically feasible power allocation (PA) technique is devised to minimize the sum bit error rate of the users and optimize the SIC-based NOMA detection at the base-station (BS). The derived closed-form expressions are corroborated through Monte Carlo simulations. It is demonstrated that these expressions can be effective for optimal uplink PA to ensure optimized SIC detection that mitigates error floors. It is also shown that significant performance improvements are achieved regardless of the users' decoding order, making uplink SIC-based NOMA a viable approach.

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Novel KLD-based Resource Allocation for Integrated Sensing and Communication

In this paper, we introduce a novel resource allocation approach for integrated sensing-communication (ISAC) using the Kullback-Leibler divergence (KLD) metric. Specifically, we consider a base-station with limited power and antenna resources serving a number of communication users and detecting multiple targets simultaneously. First, we analyze the KLD for two possible antenna deployments, which are the separated and shared deployments, then use the results to optimize the resources of the base-station through minimising the average KLD for the network while satisfying a minimum predefined KLD requirement for each user equipment (UE) and target. To this end, the optimisation is formulated and presented as a mixed integer nonlinear programming (MINLP) problem and then solved using two approaches. In the first approach, we employ a genetic algorithm, which offers remarkable performance but demands substantial computational resources; and in the second approach, we propose a rounding-based interior-point method (RIPM) that provides a more computationally-efficient alternative solution at a negligible performance loss. The results demonstrate that the KLD metric can be an effective means for optimising ISAC networks, and that both optimisation solutions presented offer superior performance compared to uniform power and antenna allocation.

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Robust Joint Active-Passive Beamforming Design for IRS-Assisted ISAC Systems

The idea of Integrated Sensing and Communication (ISAC) offers a promising solution to the problem of spectrum congestion in future wireless networks. This paper studies the integration of intelligent reflective surfaces (IRS) with ISAC systems to improve the performance of radar and communication services. Specifically, an IRS-assisted ISAC system is investigated where a multi-antenna base station (BS) performs multi-target detection and multi-user communication. A low complexity and efficient joint optimization of transmit beamforming at the BS and reflective beamforming at the IRS is proposed. This is done by jointly optimizing the BS beamformers and IRS reflection coefficients to minimize the Frobenius distance between the covariance matrices of the transmitted signal and the desired radar beam pattern. This optimization aims to satisfy the signal-to-interference-and-noise ratio (SINR) constraints of the communication users, the total transmit power limit at the BS, and the unit modulus constraints of the IRS reflection coefficients. To address the resulting complex non-convex optimization problem, an efficient alternating optimization (AO) algorithm combining fractional programming (FP), semi-definite programming (SDP), and second order cone programming (SOCP) methods is proposed. Furthermore, we propose robust beamforming optimization for IRS-ISAC systems by adapting the proposed optimization algorithm to the IRS channel uncertainties that may exist in practical systems. Using advanced tools from convex optimization theory, the constraints containing uncertainty are transformed to their equivalent linear matrix inequalities (LMIs) to account for the channels' uncertainty radius. The results presented quantify the benefits of IRS-ISAC systems under various conditions and demonstrate the effectiveness of the proposed algorithm.

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Energy-Efficient Trajectory Design of a Multi-IRS Assisted Portable Access Point

In this work, we propose a framework for energy-efficient trajectory design of an unmanned aerial vehicle (UAV)-based portable access point (PAP) deployed to serve a set of ground nodes (GNs). In addition to the PAP and GNs, the system consists of a set of intelligent reflecting surfaces (IRSs) mounted on man-made structures to increase the number of bits transmitted per Joule of energy consumed measured as the global energy efficiency (GEE). The GEE trajectory for the PAP is designed by considering the UAV propulsion energy consumption and the Peukert effect of the PAP battery, which represents an accurate battery discharge profile as a non-linear function of the UAV power consumption profile. The GEE trajectory design problem is solved in two phases: in the first, a path for the PAP and feasible positions for the IRS modules are found using a multi-tier circle packing method, and the required IRS phase shift values are calculated using an alternate optimization method that considers the interdependence between the amplitude and phase responses of an IRS element; in the second phase, the PAP flying velocity and user scheduling are calculated using a novel multilap trajectory design algorithm. Numerical evaluations show that: neglecting the Peukert effect overestimates the available flight time of the PAP; after a certain threshold, increasing the battery size reduces the available flight time of the PAP; the presence of IRS modules improves the GEE of the system compared to other baseline scenarios; the multi-lap trajectory saves more energy compared to a single-lap trajectory developed using a combination of sequential convex programming and Dinkelbach algorithm.

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On the Application of Uplink/Downlink Decoupled Access in Heterogeneous Mobile Edge Computing

Mobile edge computing (MEC) is a key player in low latency 5G networks with the task to resolve the conflict between computationally-intensive mobile applications and resource-limited mobile devices (MDs). As such, there has been intense interest in this topic, especially in multi-user single-server and homogeneous multi-server scenarios. However, the research in the heterogeneous multi-server scenario is limited, where the servers are located at small base-stations (SBSs), macro base-stations (MBSs), or the cloud with different computing and communication capabilities. On the other hand, computational-tasks offloading is limited by the type of MD-BS association with almost all previous works focusing on offloading the MD's computational tasks to the MEC servers/cloudlets at its serving BS. However, in multi-BS association, or downlink/uplink decoupled (DUDe) scenarios, an MD can be served by multiple BSs and hence has multiple offloading choices. Motivated by this, we proposed a joint BS association and subchannel allocation algorithm based on a student-project allocation (SPA) matching approach to minimize the network sum-latency, which break the constraint that one MD must connect to the same BS in the UL and DL, and jointly consider the communication and computational disparity of SBS and MBS cloudlets in heterogeneous MEC networks. Moreover, an optimal power allocation scheme is proposed to optimize the system performance subject to the predefined quality of service constraints. Our results show that the proposed scheme is superior to benchmark techniques in enabling effective use of the computational and communication resources in heterogeneous MEC networks.

cs.IT

On the Construction of Polar Codes in the Middleton Class-A Channels

Although power line communication (PLC) systems are available everywhere, unfortunately these systems are not suitable for information transmission due to the effects of the impulsive noise. Therefore, many previous studies on channel codes have been carried out for the purpose of reducing the impulsive noise in such channels. This paper investigates some methods for the construction of polar codes under PLC systems in the presence of Middleton class-A noise. We discuss here the most feasible construction methods which already have been adopted with other channels. In addition, we present an illustrative example for the construction in these methods and also we discuss a comparison between the methods in terms of performance.

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On the Feasibility of Interference Alignment in Compounded MIMO Broadcast Channels with Antenna Correlation and Mixed User Classes

This paper presents a generalized closed-form beamforming technique that can achieve the maximum degrees of freedom in compounded multiple-input multiple-output (MIMO) broadcast channels with mixed classes of multiple-antenna users. The contribution is firstly described within the context of a three-cell network and later extended to the general multi-cell scenario where we also show how to determine the conditions required to align the interference in a subspace that is orthogonal to the one reserved for the desired signals. This is then followed by an analysis of the impact of antenna correlation for different channel state information acquisition models. The proposed scheme is examined under both conventional and Large-scale MIMO systems. It will be shown that the proposed technique enables networks with any combination of user classes to achieve superior performance even under significant antenna correlation, particularly in the case of the Large-scale MIMO systems.

cs.IT

Energy-Efficient Heterogeneous Cellular Networks with Spectrum Underlay and Overlay Access

In this paper, we provide joint subcarrier assignment and power allocation schemes for quality-of-service (QoS)-constrained energy-efficiency (EE) optimization in the downlink of an orthogonal frequency division multiple access (OFDMA)-based two-tier heterogeneous cellular network (HCN). Considering underlay transmission, where spectrum-efficiency (SE) is fully exploited, the EE solution involves tackling a complex mixed-combinatorial and non-convex optimization problem. With appropriate decomposition of the original problem and leveraging on the quasi-concavity of the EE function, we propose a dual-layer resource allocation approach and provide a complete solution using difference-of-two-concave-functions approximation, successive convex approximation, and gradient-search methods. On the other hand, the inherent inter-tier interference from spectrum underlay access may degrade EE particularly under dense small-cell deployment and large bandwidth utilization. We therefore develop a novel resource allocation approach based on the concepts of spectrum overlay access and resource efficiency (RE) (normalized EE-SE trade-off). Specifically, the optimization procedure is separated in this case such that the macro-cell optimal RE and corresponding bandwidth is first determined, then the EE of small-cells utilizing the remaining spectrum is maximized. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation schemes can approach the optimal EE with each strategy being superior under certain system settings.

cs.IT