Al-Dhahir, Naofal

Permanent URI for this collectionhttps://hdl.handle.net/10735.1/6342

Naofal Al-Dhahir is an Erik Jonsson Distinguished Professor of Electrical Engineering. He is also a Fellow of the IEEE. His research interests include:

Machine/Deep learning applications
Smart grid
V2X communications
PHY security
Broadband wireless (cellular and WiFi)
Wireline (DSL and powerline) communications

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Recipient of the Signal Processing and Communications Electronics Technical Recognition Award from the Institute of Electrical and Electronics Engineers (December 2019)

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Security-Enhanced SC-FDMA Transmissions Using Temporal Artificial-Noise and Secret Key Aided Schemes
(IEEE-Inst Electrical Electronics Engineers Inc, 2019-01-19) Marzban, Mohamed F.; El Shafie, Ahmed; Al-Dhahir, Naofal; Hamila, Ridha; 0000-0002-7214-0745 (Marzban, MF); 0000-0002-7315-8242 (EL Shafie, A); 113149196515374792028 (Al-Dhahir, N); Marzban, Mohamed F.; El Shafie, Ahmed; Al-Dhahir, Naofal
We investigate the physical-layer security of uplink single-carrier frequency-division multiple-access (SC-FDMA) systems. Multiple users, Alices, send confidential messages to a common legitimate base-station, Bob, in the presence of an eavesdropper, Eve. To secure the legitimate transmissions, each user superimposes an artificial noise (AN) signal on the time-domain SC-FDMA data symbol. We reduce the computational and storage requirements at Bob's receiver by assuming simple per-sub-channel detectors. We assume that Eve has global channel knowledge of all links in addition to high computational capabilities, where she adopts high-complexity detectors such as single-user maximum likelihood (ML), multi-user minimum-mean-square-error, and multi-user ML. We analyze the correlation properties of the time-domain AN signal and illustrate how Eve can exploit them to reduce the AN effects. We prove that the number of useful AN streams that can degrade Eve's signal-to-noise ratio is dependent on the channel memories of Alices-Bob and Alices-Eve links. Furthermore, we enhance the system security for the case of partial Alices-Bob channel knowledge at Eve, where Eve only knows the precoding matrices of the data and AN signals instead of knowing the entire Alices-Bob channel matrices, and propose a hybrid security scheme that integrates temporal AN with channel-based secret key extraction.
Wiretap TDMA Networks with Energy-Harvesting Rechargeable-Battery Buffered Sources
(Institute of Electrical and Electronics Engineers Inc, 2019-01-25) El Shafie, Ahmed; Al-Dhahir, Naofal; Ding, Zhiguo; Duong, Trung Q.; Hamila, Ridha; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Naofal
We investigate the physical-layer security of an uplink wireless time-division multiple-access channel with energy-harvesting source nodes. We consider a set of source nodes equipped with rechargeable batteries and information buffers communicating confidentially with a base station, Bob, in the presence of a passive eavesdropper, Eve. An energy-harvesting rechargeable-battery cooperative jammer is assumed to assist the source nodes to confidentially send their information messages. We propose a two-level optimization formulation to improve the system's security performance. At the first optimization level, we propose a jamming scheme under energy constraints at different nodes to reduce the secrecy outage probabilities without relying on the eavesdropper's instantaneous channel state information. At the second optimization level, we optimize the number of energy packets used at the source nodes and the cooperative jammer as well as the time-slot allocation probabilities to maximize the secure throughput under the network's queues stability constraints and an application-specific secure throughput for each legitimate source node. The numerical results show the significant performance gains of our proposed optimization relative to two important benchmarks. We verify our theoretical findings through simulations and quantify the impact of key system design parameters on the security performance.
Joint Blind Identification of the Number of Transmit Antennas and MIMO Schemes Using Gerschgorin Radii and FNN
(Institute of Electrical Electronics Engineers Inc, 2018-11-13) Gao, Mingjun; Li, Yongzhao; Dobre, Octavia A.; Al-Dhahir, Naofal; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Naofal
Blind enumeration of the number of transmit antennas and blind identification of multiple-input multiple-output (MIMO) schemes are two pivotal steps in MIMO signal identification for both military and commercial applications. Conventional approaches treat them as two independent problems, namely the source number enumeration and the presence detection of space-time redundancy. In this paper, we develop a joint blind identification algorithm to determine the number of transmit antennas and MIMO schemes simultaneously. By restructuring the received signals, we derive three subspace-rank features based on the signal subspace-rank to determine the number of transmit antennas and identify space-time redundancy. Then, a Gerschgorin radii-based method and a feed-forward neural network are employed to calculate these three features, and a minimal weighted norm-1 distance metric is utilized for decision making. In particular, our approach can identify additional MIMO schemes, which most previous works have not considered, and is compatible with both single-carrier and orthogonal frequency division multiplexing (OFDM) systems. The simulation results verify the viability of our proposed approach for single-carrier and OFDM systems and demonstrate its favorable identification performance for a short observation period with acceptable complexity.
Resource Allocation For Secure Wireless Powered Integrated Multicast and Unicast Services with Full Duplex Self-Energy Recycling
(Institute of Electrical Electronics Engineers Inc, 2019-01) Chu, Zheng; Zhou, Fuhui; Xiao, Pei; Zhu, Zhengyu; Mi, De; Al-Dhahir, Naofal; Tafazolli, Rahim; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Naofal
This paper investigates a secure wireless-powered integrated service system with full-duplex self-energy recycling. Specifically, an energy-constrained information transmitter (IT), powered by a power station (PS) in a wireless fashion, broadcasts two types of services to all users: a multicast service intended for all users and a confidential unicast service subscribed to by only one user while protecting it from any other unsubscribed users and an eavesdropper. Our goal is to jointly design the optimal input covariance matrices for the energy beamforming, the multicast service, the confidential unicast service, and the artificial noises from the PS and the IT, such that the secrecy-multicast rate region (SMRR) is maximized subject to the transmit power constraints. Due to the non-convexity of the SMRR maximization (SMRRM) problem, we employ a semidefinite programming-based two-level approach to solve this problem and find all of its Pareto optimal points. In addition, we extend the SMRRM problem to the imperfect channel-state information case, where a worst-case SMRRM formulation is investigated. Moreover, we exploit the optimized transmission strategies for the confidential service and energy transfer by analyzing their own rank-one profile. Finally, numerical results are provided to validate our proposed schemes.
Machine-Learning-Based Parallel Genetic Algorithms for Multi-Objective Optimization in Ultra-Reliable Low-Latency WSNs
(Institute of Electrical Electronics Engineers Inc, 2018-12-10) Chang, Yuchao; Yuan, Xiaobing; Li, Baoqing; Niyato, Dusit; Al-Dhahir, Naofal; Al-Dhahir, Naofal
Different from conventional wireless sensor networks (WSNs), ultra-reliable and low-latency WSNs (uRLLWSNs), being an important application of 5G networks, must meet more stringent performance requirements. In this paper, we propose a novel algorithm to improve uRLLWSNs' performance by applying machine learning techniques and genetic algorithms. Using the K -means clustering algorithm to construct a 2-tier network topology, the proposed algorithm designs the fetal dataset, denoted by the population, and develops a clustering method of energy conversion to prevent overloaded cluster heads. A multi-objective optimization model is formulated to simultaneously satisfy multiple optimization objectives including the longest network lifetime and the highest network connectivity and reliability. Under this model, the principal component analysis algorithm is adopted to eliminate the various optimization objectives' dependencies and rank their importance levels. Considering the NP-hardness of wireless network scheduling, the genetic algorithm is used to identify the optimal chromosome for designing a near-optimal clustering network topology. Moreover, we prove the convergence of the proposed algorithm both locally and globally. Simulation results are presented to demonstrate the viability of the proposed algorithm compared to stateof-the-art algorithms at an acceptable computational complexity.
Joint Frame Synchronization and Channel Estimation: Sparse Recovery Approach and USRP Implementation
(Institute of Electrical and Electronics Engineers Inc., 2019-03-25) Ozdemir, O.; Anjinappa, C. K.; Hamila, R.; Al-Dhahir, Naofal; Guvenc, I.; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Naofal
Correlation-based techniques used for frame synchronization can suffer significant performance degradation over multi-path frequency-selective channels. In this paper, we propose a joint frame synchronization and channel estimation (JFSCE) framework as a remedy to this problem. This framework, however, increases the size of the resulting combined channel vector which should capture both the channel impulse response vector and the frame boundary offset and, therefore, its estimation becomes more challenging. On the other hand, because the combined channel vector is sparse, sparse channel estimation methods can be applied. We propose several JFSCE methods using popular sparse signal recovery algorithms which exploit the sparsity of the combined channel vector. Subsequently, the sparse channel vector estimate is used to design a sparse equalizer. Our simulation results and experimental measurements using software defined radios show that in some scenarios our proposed method improves the overall system performance significantly, in terms of the mean square error between the transmitted and the equalized symbols compared to the conventional method. © 2013 IEEE.
Exploiting Sparsity in Amplify-and-Forward Broadband Multiple Relay Selection
(Institute of Electrical and Electronics Engineers Inc., 2019-05-01) Hamila, R.; Al-Dhahir, Neofal; Foufou, S.; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Neofal
Cooperative communication has attracted significant attention in the last decade due to its ability to increase the spatial diversity order with only single-antenna nodes. However, most of the techniques in the literature are not suitable for large cooperative networks such as device-to-device and wireless sensor networks that are composed of a massive number of active devices, which significantly increases the relay selection complexity. Therefore, to solve this problem and enhance the spatial and frequency diversity orders of large amplify and forward cooperative communication networks, in this paper, we develop three multiple relay selection and distributed beamforming techniques that exploit sparse signal recovery theory to process the subcarriers using the low complexity orthogonal matching pursuit algorithm (OMP). In particular, by separating all the subcarriers or some subcarrier groups from each other and by optimizing the selection and beamforming vector(s) using OMP algorithm, a higher level of frequency diversity can be achieved. This increased diversity order allows the proposed techniques to outperform existing techniques in terms of bit error rate at a lower computation complexity. A detailed performance-complexity tradeoff, as well as Monte Carlo simulations, are presented to quantify the performance and efficiency of the proposed techniques. © 2013 IEEE.
Opportunistic Ambient Backscatter Communication in RF-Powered Cognitive Radio Networks
(Institute of Electrical and Electronics Engineers Inc.) Kishore, R.; Gurugopinath, S.; Sofotasios, P. C.; Muhaidat, S.; Al-Dhahir, Naofal; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Naofal
In the present contribution, we propose a novel opportunistic ambient backscatter communication (ABC) framework for radio frequency (RF)-powered cognitive radio (CR) networks. This framework considers opportunistic spectrum sensing integrated with ABC and harvest-then-transmit (HTT) operation strategies. Novel analytic expressions are derived for the average throughput, the average energy consumption and the energy efficiency in the considered set up. These expressions are represented in closed-form and have a tractable algebraic representation which renders them convenient to handle both analytically and numerically. In addition, we formulate an optimization problem to maximize the energy efficiency of the CR system operating in mixed ABC– and HTT– modes, for a given set of constraints including primary interference and imperfect spectrum sensing constraints. Capitalizing on this, we determine the optimal set of parameters which in turn comprise the optimal detection threshold, the optimal degree of trade-off between the CR system operating in the ABC– and HTT– modes and the optimal data transmission time. Extensive results from respective computer simulations are also presented for corroborating the corresponding analytic results and to demonstrate the performance gain of the proposed model in terms of energy efficiency.
Sensing-Throughput Tradeoff for Superior Selective Reporting-Based Spectrum Sensing in Energy Harvesting HCRNs
(Institute uf Electrical and Electronics Engineers Inc.) Kishore, R.; Gurugopinath, S.; Muhaidat, S.; Sofotasios, P. C.; Dobre, O. A.; Al-Dhahir, Naofal; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Naofal
In this paper, we investigate the performance of conventional cooperative sensing (CCS) and superior selective reporting (SSR)-based cooperative sensing in an energy harvesting-enabled heterogeneous cognitive radio network (HCRN). In particular, we derive expressions for the achievable throughput of both schemes and formulate nonlinear integer programming problems, in order to find the throughput-optimal set of spectrum sensors scheduled to sense a particular channel, given primary user (PU) interference and energy harvesting constraints. Furthermore, we present novel solutions for the underlying optimization problems based on the cross-entropy (CE) method, and compare the performance with exhaustive search and greedy algorithms. Finally, we discuss the tradeoff between the average achievable throughput of the SSR and CCS schemes, and highlight the regime where the SSR scheme outperforms the CCS scheme. Notably, we show that there is an inherent tradeoff between the channel available time and the detection accuracy. Our numerical results show that, as the number of spectrum sensors increases, the channel available time gains a higher priority in an HCRN, as opposed to detection accuracy. ©2019 IEEE
Energy Efficiency Analysis of Collaborative Compressive Sensing for Cognitive Radio Networks
(Institute of Electrical and Electronics Engineers Inc.) Kishore, R.; Gurugopinath, S.; Muhaidat, S.; Sofotasios, P. C.; Dianati, M.; Al-Dhahir, Naofal; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Naofal
We investigate the energy efficiency of a conventional collaborative compressed sensing (CCCS) scheme in cognitive radio networks. In particular, we derive expressions for the throughput, energy consumption and energy efficiency, and analyze the trade-off between the achievable throughput and the energy consumption of the underlying CCCS scheme. Furthermore, we formulate a multiple variable non-convex optimization problem to determine the optimum compression level that maximizes the energy efficiency, subject to interference constraints. We propose a sub-optimal solution based on tight approximations to simplify the aforementioned optimization problem, and further demonstrate that the energy efficiency achieved by the CCCS scheme is higher than that of conven- tional collaborative sensing scheme, under the same predefined conditions. It is further shown that the increase in the energy efficiency of CCCS scheme is due to the considerable decrease in the energy consumption, which is particularly noticeable with a large number of sensors. © 2018 IEEE.
Sparsity-Based Joint NBI and Impulse Noise Mitigation in Hybrid PLC-Wireless Transmissions
(Institute of Electrical and Electronics Engineers Inc.) Elgenedy, Mahmoud; Mokhtar, M.; Hamila, R.; Bajwa, W. U.; Ibrahim, A. S.; Al-Dhahir, Naofal; 0000-0003-3402-5188 (Elgenedy, M); 113149196515374792028 (Al-Dhahir, N); Elgenedy, Mahmoud; Al-Dhahir, Naofal
We propose a new sparsity-aware framework to model and mitigate the joint effects of narrow-band interference (NBI) and impulsive noise (IN) in hybrid powerline and unlicensed wireless communication systems. The proposed mitigation techniques, based on the principles of compressive sensing (CS), exploit the inherent (non-contiguous or contiguous) sparse structures of NBI and IN in the frequency and time domains, respectively. For the non-contiguous NBI and IN, we develop a multi-level orthogonal matching pursuit recovery algorithm that exploits prior knowledge about the sparsity level at each receive antenna and powerline to further reduce computational complexity without performance loss. In addition, for the non-contiguous asynchronous NBI scenario, we investigate the application of time-domain windowing to enhance the NBI’s sparsity and, hence, improve the NBI mitigation performance. For the contiguous NBI and IN scenario, we estimate the NBI and IN signals by modeling their burstiness as block-sparse vectors with and without prior knowledge of the bursts’ boundaries. Moreover, we show how to exploit the spatial correlations of the NBI and IN across the receive antennas and powerlines to convert a non-contiguous NBI and IN problem to a block-sparse estimation problem with much lower complexity. Furthermore, we investigate a Bayesian linear minimum mean square error based approach for estimating both non-contiguous and contiguous NBI and IN based on their second-order statistics to further improve the estimation performance. Finally, our numerical results illustrate the superiority of the joint processing of our proposed NBI and IN sparsity-based mitigation techniques compared to separate processing of the wireless and powerline received signals.
Secure Sum-Rate Optimal MIMO Multicasting over Medium-Voltage NB-PLC Networks
(Institute of Electrical and Electronics Engineers Inc.) Elsamadouny, Ahmed; El Shafie, Ahmed; Abdallah, M.; Al-Dhahir, Naofal; 0000-0002-2716-7658 (Elsamadouny, A); 113149196515374792028 (Al-Dhahir, N); Elsamadouny, Ahmed; El Shafie, Ahmed; Al-Dhahir, Naofal
We propose a multiple-input multiple-output orthogonal frequency-division multiplexing transceiver for narrowband power-line communication applications in multi-user medium-voltage multicasting networks. The 3-phase medium-voltage multicasting network is modeled as a 2-input/3-output multiple-input multiple-output frequency-selective channel over the 3-500 kHz frequency band. We design the optimal spatial precoder, spatial power allocation, and frequency bit loading profile which maximize the sum-rate of the multicasting groups. In addition, we propose two schemes to secure data transmission through the two-group multicasting network. The first scheme secures the network when the eavesdropper is a user in one of the two multicasting groups and, hence, its channel state information is known at the transmitter. The second scheme secures the multicasting network from external passive eavesdroppers and, hence, the channels between the transmitter and the eavesdroppers are assumed to be unknown at the transmitter. The secrecy rate is evaluated for both scenarios. ©2016 IEEE.
Robust Resource Allocation for MISO Cognitive Radio Networks under Two Practical Non-Linear Energy Harvesting Models
(Institute of Electrical and Electronics Engineers Inc.) Zhang, X.; Wang, Y.; Zhou, F.; Al-Dhahir, Naofal; Deng, X.; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Naofal
To achieve a good tradeoff between the consumed power and the harvested power, a robust resource optimization problem is studied in a multiple-input single-output cognitive radio network with simultaneous wireless information and power transfer under imperfect channel state information. Unlike most of the existing works that assume an ideal linear energy harvesting (EH) model, we assume two practical non-linear EH models. In order to solve the resulting challenging non-convex problem, we propose an algorithm based on successive convex approximation and prove that a rank-one solution is obtained in each iteration of the proposed algorithm. Our simulation results quantify the effect of the sensitivity threshold of the EH circuit on the harvested power. ©2018 IEEE
Power Splitting-Based SWIPT with Dual-Hop DF Relaying in the Presence of a Direct Link
(Institute of Electrical and Electronics Engineers Inc.) Ye, Y.; Li, Y.; Zhou, F.; Al-Dhahir, Naofal; Zhang, H.; Al-Dhahir, Naofal
This letter investigates the outage performance of dual-hop decode and forward relay systems in the presence of a direct link between the source and the destination, where simultaneous wireless information and power transfer is exploited at the relay by using a static/dynamic power splitting (PS) scheme. An analytical expression for the outage probability is derived to determine the optimal static PS ratio. Moreover, we study the dynamic PS scheme and derive a closed-form expression for the optimal dynamic PS ratio to minimize the outage probability at a given target rate. Furthermore, an analytical expression for the outage probability with the optimal dynamic PS ratio is also presented. It is shown that a full diversity gain can be achieved in the investigated system with static/dynamic PS scheme, and that the dynamic PS scheme outperforms the static PS scheme. ©2018 IEEE
Outage Probability of Single Carrier NOMA Systems under I/Q Imbalance
(Institute of Electrical and Electronics Engineers Inc.) Selim, B.; Muhaidat, S.; Sofotasios, P. C.; Sharif, B. S.; Stouraitis, T.; Karagiannidis, G. K.; Al-Dhahir, Naofal; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Naofal
Non-orthogonal multiple access (NOMA) has been recently proposed as a viable technology that has the potential to improve the spectral efficiency of fifth generation (5G) wireless networks and beyond. However, in practical communication scenarios, transceiver architectures inevitably suffer from radio-frequency (RF) front-end related impairments that can lead to non-negligible degradation of the overall system performance. In this context, in-phase/quadrature-phase imbalance (IQI) constitutes a major impairment in direct-conversion transceivers. Based on this, the present contribution quantifies the effects of IQI on the performance of NOMA based systems under multipath fading conditions. This is realized by first deriving novel analytic expressions for the signal-to-interference-plus-noise ratio and the outage probability of NOMA systems subject to IQI at the transmitter and/or the receiver sites. Capitalizing on these results, we demonstrate that the effects of IQI differ considerably between the different NOMA users and depending on the considered system's parameters. © 2018 IEEE.
Impact of Passive and Active Security Attacks on MIMO Smart Grid Communications
(Institute of Electrical and Electronics Engineers Inc.) El Shafie, Ahmed; Chihaoui, H.; Hamila, R.; Al-Dhahir, Naofal; Gastli, A.; Ben-Brahim, L.; 0000-0002-7315-8242 (El Shafie, A); El Shafie, Ahmed; Al-Dhahir, Naofal
We consider multiple source nodes (consumers) communicating wirelessly their energy demands to the meter data-management system (MDMS) over the subarea gateway(s). We quantify the impact of passive and active security attacks on the reliability and security of the wireless communications system and the energy-demand estimation error cost in dollars incurred by the utility. We adopt a multiple-input multiple-output (MIMO) multiantenna-eavesdropper wiretap channel model. To secure the MIMO wireless communication system, the legitimate nodes generate artificial noise signals to mitigate the effect of the passive eavesdropping security attacks. Furthermore, we propose a redundant gateway design where multiple gateways are assumed to coexist in each subarea to forward the consumers’ energy-demand messages. We quantify the redundant designs impact on the communication reliability between the consumers and the MDMS and on the energy-demand estimation error cost.
A Joint Unsupervised Learning and Genetic Algorithm Approach for Topology Control in Energy-Efficient Ultra-Dense Wireless Sensor Networks
(Institute of Electrical and Electronics Engineers Inc.) Chang, Y.; Yuan, X.; Li, B.; Niyato, D.; Al-Dhahir, Naofal; Al-Dhahir, Naofal
Energy efficiency is a key performance metric for ultra-dense wireless sensor networks. In this letter, an unsupervised learning approach for topology control is proposed to prolong the lifetime of ultra-dense wireless sensor networks by balancing energy consumption. By encoding sensors as genes according to the network clusters, the proposed genetic-based algorithm learns an optimum chromosome to construct a close-to-optimum network topology using unsupervised learning in probability. Moreover, it schedules some of the cluster members to sleep to conserve the node energy using geographically adaptive fidelity. Simulation results demonstrate the superior performance of the proposed algorithm by improving energy efficiency in comparison with state-of-the-art algorithms at an acceptable computational complexity.
ADMM for Joint Data and Off-Grid NBI Recovery in OFDM Systems
(Institute of Electrical and Electronics Engineers Inc.) Al-Tous, H.; Barhumi, I.; Kalbat, A.; Al-Dhahir, Naofal; 113149196515374792028 (Al-Dhahir, N); Al-Dhahir, Naofal
Joint data and off-grid narrow-band interference (NBI) recovery is investigated in orthogonal-frequency-division-multiplexing (OFDM) systems using compressive-sensing (CS) framework. The joint recovery problem is formulated as a convex optimization problem of three weighted norms. A reduced computational complexity and scalable algorithm is proposed to solve the recovery problem based on the alternating-direction-method-of-multipliers (ADMM). Simulation results, show that the average-run-time of solving the joint recovery problem using the proposed ADMM algorithm is much less than the average-run-time of the interior point method.
Sparse Equalizers for OFDM Signals with Insufficient Cyclic Prefix
(IEEE - Inst Electrical Electronics Engineers Inc) Samara, Lutfi; Alabassi, Abubakr O.; Hamila, Ridha; Al-Dhahir, Naofal; Al-Dhahir, Naofal
The cyclic prefix (CP) is appended in orthogonal frequency division multiplexing (OFDM) signals to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) induced by the communication channel, which limits its spectral efficiency. Therefore, inserting an insufficient CP and equalizing the resulting ICI and ISI is a method that has been circulating the literature for a while, aiming at increasing the efficiency of OFDM systems. In this paper, we propose a reduced-complexity sparse linear equalizer and a decision-feedback equalizer for OFDM signals with insufficient CP. A performance-complexity trade-off is highlighted, where we show that it is possible to equalize the received signal with a reduced complexity equalizer while having a limited performance loss. Our proposed equalizer designs are not only less complex to realize, but are shown to provide a higher data rate. The proposed equalizers are further evaluated in terms of the worst-case coherence, a metric determining the effectiveness of our used approach. Numerical results show that we can significantly and reliably reduce the order of the design complexity while performing very close to the conventional complex optimal equalizers.
Cyclostationary Noise Mitigation for SIMO Powerline Communications
(IEEE-Inst Electrical Electronics Engineers Inc) Elgenedy, Mahmoud; Sayed, Mostafa; Al-Dhahir, Naofal; Chabaan, Rakan C.; 0000 0003 5178 379X (Al-Dhahir, N); 0000-0002-1866-0272 (Sayed, M); 113149196515374792028 (Al-Dhahir, N); Elgenedy, Mahmoud; Sayed, Mostafa; Al-Dhahir, Naofal
The cyclostationary noise in low-voltage narrowband powerline communications (NB-PLC) severely degrades the communication reliability. In this paper, we adopt single-input multi-output (SIMO) transmission to enhance the reliability of NB-PLC. Considering the SIMO receiver structure, we exploit the NB-PLC noise cyclostationarity and the high spatial correlations across multiple receive phases to design practical and efficient noise mitigation techniques. In particular, we propose two time-domain frequency shift (FRESH) filtering-based cyclostationary signal recovery techniques with different performance and complexity levels. The proposed time-domain-based FRESH filtering techniques minimize the mean squared error in estimating the orthogonal frequency division multiplexing (OFDM) information signal in the time-domain The FRESH filtering exploits the cyclic auto-correlation of both the NB-PLC noise and the OFDM information signal in addition to their cyclic cross-correlation across the receive phases. Moreover, we propose a frequency-domain-based cyclostationary noise mitigation technique that minimizes the mean squared error in estimating the OFDM information signal in the frequency-domain The proposed frequency domain-based technique exploits the cyclostationarity of the noise to estimate its power spectral density as well as the cross-correlation, per frequency subchannel, over multiple stationary noise temporal regions. Our proposed SIMO NB-PLC noise mitigation techniques are shown via simulation results conducted using noise field measurements to achieve considerable performance gains over single-input single-output techniques. In addition, we show that our proposed techniques achieve considerable performance gains over the conventional SIMO maximal-ratio-combiner designed assuming stationary noise.

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