arXiv subjects

Anas Chaaban

Publications and source records attributed to Anas Chaaban.

At least 37 records · Page 2Linked to original sources

arXiv2023

Analysis of One-Bit Quantized Linear Precoding Schemes in Multi-Cell Massive MIMO Downlink

This work studies a multi-cell one-bit massive multiple-input multiple-output (MIMO) system that employs one-bit analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) at each base station (BS). We utilize Bussgang decomposition to derive downlink signal-to-quantization-plus-interference-plus-noise ratio (SQINR) and ergodic achievable rate expressions under one-bit quantized maximum ratio transmission (MRT) and zero-forcing (ZF) precoding schemes considering scenarios with and without pilot contamination (PC) in the derived channel estimates. The results are also simplified for the mixed architecture that employs full resolution (FR) ADCs and one-bit DACs, and the conventional architecture that employs FR ADCs and DACs. The SQINR is shown to decrease by a factor of $2/π$ and $4/π^2$ in the one-bit setting compared to that achieved in the mixed setting and conventional setting respectively under MRT precoding without PC. Interestingly, the decrease in SQINR is less when we consider PC, which is shown to adversely impact the conventional system more than the one-bit system. Similar insights are obtained under ZF precoding with the decrease in the SQINR with the use of one-bit ADCs and DACs being more pronounced. We utilize the derived expressions to yield performance insights related to power efficiency, the numbers of antennas needed by the three architectures to achieve the same sum-rate, and energy efficiency.

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arXiv2023

Rate Outage and Meta-Distribution for Uplink Networks in Finite Block-Length Regime

With the expected proliferation of delay constrained applications, future communication technologies are pushed towards using short codes. The performance using short codes cannot be inferred through classical channel capacity analysis, which intrinsically assumes long codes and vanishing frame error rate (FER). This paper studies the performance of an uplink large-scale network in the finite blocklength regime. Bounds on the spatially averaged rate outage probability as well as the coding rate meta distribution are derived. The results reveal the exact achievable rate for a given blocklength and FER, and demonstrate the discrepancy between the actual network rate and idealistic classical channel capacity.

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arXiv2023

Hybrid Digital-Wave Domain Channel Estimator for Stacked Intelligent Metasurface Enabled Multi-User MISO Systems

Stacked intelligent metasurface (SIM) is an emerging programmable metasurface architecture that can implement signal processing directly in the electromagnetic wave domain, thereby enabling efficient implementation of ultra-massive multiple-input multiple-output (MIMO) transceivers with a limited number of radio frequency (RF) chains. Channel estimation (CE) is challenging for SIM-enabled communication systems due to the multi-layer architecture of SIM, and because we need to estimate large dimensional channels between the SIM and users with a limited number of RF chains. To efficiently solve this problem, we develop a novel hybrid digital-wave domain channel estimator, in which the received training symbols are first processed in the wave domain within the SIM layers, and then processed in the digital domain. The wave domain channel estimator, parametrized by the phase shifts applied by the meta-atoms in all layers, is optimized to minimize the mean squared error (MSE) using a gradient descent algorithm, within which the digital part is optimally updated. For an SIM-enabled multi-user system equipped with 4 RF chains and a 6-layer SIM with 64 meta-atoms each, the proposed estimator yields an MSE that is very close to that achieved by fully digital CE in a massive MIMO system employing 64 RF chains. This high CE accuracy is achieved at the cost of a training overhead that can be reduced by exploiting the potential low rank of channel correlation matrices.

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arXiv2023

Unit Cell Phase-Frequency Profile Optimization in RIS-Assisted Wide-Band OFDM Systems

The reflection characteristics of a reconfigurable intelligent surface (RIS) depend on the phase response of the constituent unit cells, which is necessarily frequency dependent. This paper investigates the role of an RIS constituting unit cells with different phase-frequency profiles in a wide-band orthogonal frequency division multiplexing (OFDM) system to improve the achievable rate. We first propose a mathematical model for the phase-frequency relationship parametrized by the phase-frequency profile's slope and phase-shift corresponding to a realizable resonant RIS unit cell. Then, modelling each RIS element with $b$ control bits, we propose a method for selecting the parameter pairs to obtain a set of $2^b$ phase-frequency profiles. The proposed method yields an RIS design that outperforms existing designs over a wide range of user locations in a single-input, single-output (SISO) OFDM system. We then propose a low-complexity optimization algorithm to maximize the data rate through the joint optimization of (a) power allocations across the sub-carriers and (b) phase-frequency profile for each RIS unit cell from the available set. The analysis is then extended to a multi-user multiple-input single-output (MISO) OFDM scenario. Numerical results show an improvement in the coverage and achievable rates under the proposed framework as compared to single-slope phase-frequency profiles.

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arXiv2023

Enhancing Secret Key Generation in Block Fading Channels using Reconfigurable Intelligent Surfaces

Physical layer security (PLS) is superior to classical cryptography techniques due to its notion of perfect secrecy and independence to an eavesdropper's computational power. One form of PLS arises when Alice and Bob (the legitimate users) exchange signals to extract a common key from the random common channels. The drawback of extracting keys from wireless channels is the ample dependence on the dynamicity and fluctuations of the radio channel. However, some radio channels are constant such as line of sight (LoS) and can be estimated by Eve (an illegitimate user), or can be quite static in behaviour due to the presence low-mobility users thus restricting the amount of randomness. This in turn lowers the secret key rate (SKR) defined as the number of bits of key generated per channel use. In this work, we aim to address this challenge by using a reconfigurable intelligent surface (RIS) to produce random phases at certain carefully curated intervals such that it disrupts the channel in low entropy environments. We propose an RIS assisted key generation method, study its performance, and compare with benchmarks to observe the benefit of using an RIS while considering various important metrics such as key mismatch rate and average secret key throughput. Simulations are made to validate our theoretical findings showing an improvement in performance when an RIS is deployed.

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arXiv2023

Reconfigurable Intelligent Surfaces Assisted Communication Under Different CSI Assumptions

This work studies the net sum-rate performance of a distributed reconfigurable intelligent surfaces (RISs)-assisted multi-user multiple-input-single-output (MISO) downlink communication system under imperfect instantaneous-channel state information (I-CSI) to implement precoding at the base station (BS) and statistical-CSI (S-CSI) to design the RISs phase-shifts. Two channel estimation (CE) protocols are considered for I-CSI acquisition: (i) a full CE protocol that estimates all direct and RISs-assisted channels over multiple training sub-phases, and (ii) a low-overhead direct estimation (DE) protocol that estimates the end-to-end channel in a single sub-phase. We derive the asymptotic equivalents of signal-to-interference-plus-noise ratio (SINR) and ergodic net sum-rate under both protocols for given RISs phase-shifts, which are then optimized based on S-CSI. Simulation results reveal that the low-complexity DE protocol yields better net sum-rate than the full CE protocol when used to obtain CSI for precoding. A benchmark full I-CSI based RISs design is also outlined and shown to yield higher SINR but lower net sum-rate than the S-CSI based RISs design.

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arXiv2023

Distributed Reconfigurable Intelligent Surfaces Assisted Wireless Communication: Asymptotic Analysis under Imperfect CSI

This work studies the net sum-rate performance of a distributed reconfigurable intelligent surfaces (RISs)-assisted multi-user multiple-input-single-output (MISO) downlink communication system under imperfect instantaneous-channel state information (I-CSI) to implement precoding at the base station (BS) and statistical-CSI (S-CSI) to design the RISs phase-shifts. Two channel estimation (CE) protocols are considered for I-CSI acquisition: (i) a full CE protocol that estimates all direct and RISs-assisted channels over multiple training sub-phases, and (ii) a low-overhead direct estimation (DE) protocol that estimates the end-to-end channel in a single sub-phase. We derive the deterministic equivalents of signal-to-interference-plus-noise ratio (SINR) and ergodic net sum-rate under Rayleigh and Rician fading and both CE protocols, for given RISs phase-shifts, which are then optimized based on S-CSI. Simulation results reveal that the low-complexity DE protocol yields better net sum-rate than the full CE protocol when used to obtain CSI for precoding. A benchmark full I-CSI based RISs design is also outlined and shown to yield higher SINR but lower net sum-rate than the S-CSI based RISs design due to the large overhead associated with full I-CSI acquisition. Therefore the proposed DE-S-CSI based design for precoding and reflect beamforming achieves high net sum-rate with low complexity, overhead and power consumption.

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arXiv2023

Finite Blocklength Regime Performance of Downlink Large Scale Networks

Some emerging 5G and beyond use-cases impose stringent latency constraints, which necessitates a paradigm shift towards finite blocklength performance analysis. In contrast to Shannon capacity-achieving codes, the codeword length in the finite blocklength regime (FBR) is a critical design parameter that imposes an intricate tradeoff between delay, reliability, and information coding rate. In this context, this paper presents a novel mathematical analysis to characterize the performance of large-scale downlink networks using short codewords. Theoretical achievable rates, outage probability, and reliability expressions are derived using the finite blocklength coding theory in conjunction with stochastic geometry, and compared to the performance in the asymptotic regime (AR). Achievable rates under practical modulation schemes as well as multilevel polar coded modulation (MLPCM) are investigated. Numerical results provide theoretical performance benchmarks, highlight the potential of MLPCM in achieving close to optimal performance with short codewords, and confirm the discrepancy between the performance in the FBR and that predicted by analysis in the AR. Finally, the meta distribution of the coding rate is derived, providing the percentiles of users that achieve a predefined target rate in a network.

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arXiv2023

Coding for the Gaussian Channel in the Finite Blocklength Regime Using a CNN-Autoencoder

The development of delay-sensitive applications that require ultra high reliability created an additional challenge for wireless networks. This led to Ultra-Reliable Low-Latency Communications, as a use case that 5G and beyond 5G systems must support. However, supporting low latency communications requires the use of short codes, while attaining vanishing frame error probability (FEP) requires long codes. Thus, developing codes for the finite blocklength regime (FBR) achieving certain reliability requirements is necessary. This paper investigates the potential of Convolutional Neural Networks autoencoders (CNN-AE) in approaching the theoretical maximum achievable rate over a Gaussian channel for a range of signal-to-noise ratios at a fixed blocklength and target FEP, which is a different perspective compared to existing works that explore the use of CNNs from bit-error and symbol-error rate perspectives. We explain the studied CNN-AE architecture, evaluate it numerically, and compare it to the theoretical maximum achievable rate and the achievable rates of polar coded quadrature amplitude modulation (QAM), Reed-Muller coded QAM, multilevel polar coded modulation, and a TurboAE-MOD scheme from the literature. Numerical results show that the CNN-AE outperforms these benchmark schemes and approaches the theoretical maximum rate, demonstrating the capability of CNN-AEs in learning good codes for delay-constrained applications.

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arXiv2023

Binary Modelling and Capacity-Approaching Coding for the IM/DD Channel

The paper provides a new perspective on peak- and average-constrained Gaussian channels. Such channels model optical wireless communication (OWC) systems which employ intensity-modulation with direct detection (IM/DD). First, the paper proposes a new, capacity-preserving vector binary channel (VBC) model, consisting of dependent binary noisy bit-pipes. Then, to simplify coding over this VBC, the paper proposes coding schemes with varying levels of complexity, building on the capacity of binary-symmetric channels (BSC) and channels with state. The achievable rates are compared to capacity and capacity bounds, showing that coding for the BSC with state over the VBC achieves rates close to capacity at moderate to high signal-to-noise ratio (SNR), whereas simpler schemes achieve lower rates at lower complexity. The presented coding schemes are realizable using capacity-achieving codes for binary-input channels, such as polar codes. Numerical results are provided to validate the theoretical results and demonstrate the applicability of the proposed schemes.

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arXiv2023

Performance Analysis of Zero-Forcing Precoding in Multi-Cell One-Bit Massive MIMO Downlink

This work investigates the downlink performance of a multi-cell massive multiple-input multiple-output (MIMO) system that employs one-bit analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) in the receiving and transmitting radio frequency (RF) chains at each base station (BS) in order to reduce the power consumption. We utilize Bussgang decomposition to derive the minimum mean squared error (MMSE) channel estimates at each BS based on the quantized received uplink training signals, and the asymptotic closed-form expressions of the achievable downlink rates under one-bit quantized zero-forcing (ZF) precoding implemented using the estimated channels. The derived expressions explicitly show the impact of quantization noise, thermal noise, pilot contamination, and interference, and are utilized to study the number of additional antennas needed at each BS of the one-bit MIMO system to perform as well as the conventional MIMO system. Numerical results verify our analysis, and reveal that despite needing more antennas to achieve the same sum average rate, the one-bit massive MIMO system is more energy-efficient than the conventional system, especially at high sampling frequencies.

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arXiv2023

Precoding for a Class of Peak-Constrained Dirty Paper Channels with a Discrete State

The dirty paper channel (DPC) under a peak amplitude constraint arises in an optical wireless broadcast channel (BC), where the state at one receiver is the transmitted signal intended for the other receiver(s). This paper studies a class of peak-constrained DPC that is applicable to the optical wireless BC, where the channel state (i.e, `dirt') takes values from some evenly-spaced grid. For the discrete-state DPC studied this paper, a capacity upper bound is obtained from its state-free counterpart. To lower bound its capacity, classical dirty paper coding schemes are revisited, including Costa's coding for DPC and Tomlinson-Harashima (TH) precoding, which serves as benchmark schemes. To improve the benchmark performance, two new precoding schemes are proposed for the discrete-state DPC. Although the proposed schemes do not achieve the state-free capacity contrary to what is known about the Costa's DPC, achievable rates within a small gap to the state-free capacity are demonstrated for the discrete-state DPC. Using the proposed precoding scheme in a two-user peak-constrained Gaussian BC, a new capacity inner bound (IB) is obtained, and is shown to outperform the truncated Gaussian (TG) based IB and is comparable to the best-known IB.

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arXiv2022

Improving UAV Communication in Cell Free MIMO Using a Reconfigurable Intelligent Surface

Communication with unmanned aerial vehicles (UAVs) in current terrestrial networks suffers from poor signal strength due to the down-tilt of the access points (APs) that are optimized to serve ground users ends (GUEs). To solve this, one could tilt the AP antenna upwards or allocate more power to serve the UAV. However, this negatively affects GUE downlink (DL) rates. In this paper, we propose to solve this challenge using a reconfigurable intelligent surface (RIS) to enhance the UAV communication while preserving the 3GPP- prescribed downwards antenna tilt and potentially improving the DL performance of the GUE. We show that under conjugate beamforming (CB) precoding and proper power split between GUEs and the UAV at the APs, an RIS with phase-shifts configured to reflect radio signals towards the UAV can significantly improve the UAV DL throughput while simultaneously benefiting the GUEs. The presented numerical results show that the RIS- aided system can serve a UAV with a required data rate while improving the GUEs DL performance relative to that in a CF- MIMO system without a UAV and an RIS. We support this conclusion through simulations under a varying numbers of RIS reflecting elements, UAV heights, and power split factor.

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arXiv2022

On Achievable Rates of Evenly-Spaced Discrete Uniform Distributions in the IM/DD Broadcast Channel

In optical wireless communications, a broadcast channel (BC) employing intensity modulation and direct detection (IM/DD) is often modelled as a peak-constrained BC. A closed-form expression for its capacity region of the peak-constrained BC is not known. This paper presents an analytical capacity inner bound for the peak-constrained Gaussian BC achieved by a class of discrete input distribution, specifically, the evenly-spaced discrete uniform distribution (ESDU). In contrast to the continuous input distribution that provides the benchmark, ESDU is more promising in the application of peak-constrained Gaussian channels. The newly obtained capacity inner bound is easily-computable and is numerically shown to be tighter than the benchmark. Besides, we remark the newly developed analytical upper bound for the ESDU rate, which is tight in all tested settings.

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arXiv2022

User Association in User-Centric Hybrid VLC/RF Cell-Free Massive MIMO Systems

A continuous goal in all communication systems is to enhance the users experience and provide them with the highest possible data rates. Recently, the concept of cell-free massive MIMO (CF-mMIMO) systems has been considered to enhance the performance of systems that operate merely with Radio Frequency (RF) or visible light communication (VLC) technologies. In this paper, a hybrid VLC/RF cell-free massive MIMO system is proposed where an RF cell-free network and a VLC cell-free network coexist to serve users. The idea is to utilize the benefits of each network and balance the load aiming at maximizing the system's sum-rate. The system is evaluated using zero-forcing (ZF) precoding scheme. Two user association algorithms are proposed to assign users to either the VLC or the RF networks. In addition, two user-centric clustering approaches are proposed and evaluated. Simulation results show that the proposed association algorithms significantly outperform a random network association of users in terms of sum-rate. Results also show great potential for the proposed system compared to standalone cell-free networks.

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arXiv2022

Capacity Bounds for the Two-User IM/DD Interference Channel

This paper studies the capacity of the two-user intensity-modulation/direct-detection (IM/DD) interference channel (IC), which is relevant in the context of multi-user optical wireless communications. Despite some known single-letter capacity characterizations for general discrete-memoryless ICs, a computable capacity expression for the IM/DD IC is missing. In this paper, we provide tight and easily computable inner and outer bounds for a general two-user IM/DD IC under peak and average optical intensity constraints. The bounds enable characterizing the asymptotic sum-rate capacity in the strong and weak interference regimes, as well as the generalized degrees of freedom (GDoF) in the symmetric case. Using the obtained bounds, the GDoF of the IM/DD IC is shown to have a `W' shape similar to the Gaussian IC with power constraints. The obtained bounds are also evaluated numerically in different interference regimes to show their tightness, and used to study the performance of on-chip and indoor OWC systems.

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arXiv2022

Decentralized Aggregation for Energy-Efficient Federated Learning via Overlapped Clustering and D2D Communications

Federated learning (FL) has emerged as a distributed machine learning (ML) technique to train models without sharing users' private data. In this paper, we propose a decentralized FL scheme that is called \underline{f}ederated \underline{l}earning \underline{e}mpowered \underline{o}verlapped \underline{c}lustering for \underline{d}ecentralized aggregation (FL-EOCD). The introduced FL-EOCD leverages device-to-device (D2D) communications and overlapped clustering to enable decentralized aggregation, where a cluster is defined as a coverage zone of a typical device. The devices located on the overlapped clusters are called bridge devices (BDs). In the proposed FL-EOCD scheme, a clustering topology is envisioned where clusters are connected through BDs, so as the aggregated models of each cluster is disseminated to the other clusters in a decentralized manner without the need for a global aggregator or an additional hop of transmission. Unlike the star-based FL, the proposed FL-EOCD scheme involves a large number of local devices by reusing the RRBs in different non-adjacent clusters. To evaluate our proposed FL-EOCD scheme as opposed to baseline FL schemes, we consider minimizing the overall energy-consumption of devices while maintaining the convergence rate of FL subject to its time constraint. To this end, a joint optimization problem, considering scheduling the local devices/BDs to the CHs and computation frequency allocation, is formulated, where an iterative solution to this joint problem is devised. Extensive simulations are conducted to verify the effectiveness of the proposed FL-EOCD algorithm over FL conventional schemes in terms of energy consumption, latency, and convergence rate.

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arXiv2022

Alternating Channel Estimation and Prediction for Cell-Free mMIMO with Channel Aging: A Deep Learning Based Scheme

In large scale dynamic wireless networks, the amount of overhead caused by channel estimation (CE) is becoming one of the main performance bottlenecks. This is due to the large number users whose channels should be estimated, the user mobility, and the rapid channel change caused by the usage of the high-frequency spectrum (e.g. millimeter wave). In this work, we propose a new hybrid channel estimation/prediction (CEP) scheme to reduce overhead in time-division duplex (TDD) wireless cell-free massive multiple-input-multiple-output (mMIMO) systems. The scheme proposes sending a pilot signal from each user only once in a given number (window) of coherence intervals (CIs). Then minimum mean-square error (MMSE) estimation is used to estimate the channel of this CI, while a deep neural network (DNN) is used to predict the channels of the remaining CIs in the window. The DNN exploits the temporal correlation between the consecutive CIs and the received pilot signals to improve the channel prediction accuracy. By doing so, CE overhead is reduced by at least 50 percent at the expense of negligible CE error for practical user mobility settings. Consequently, the proposed CEP scheme improves the spectral efficiency compared to the conventional MMSE CE approach, especially when the number of users is large, which is demonstrated numerically.

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