arXiv subjects

Amine Maaref

Publications and source records attributed to Amine Maaref.

9 recordsLinked to original sources

arXiv2023

Adversarial Score-Based Generative Models for MMSE-achieving AmBC Channel Estimation

This letter presents a pioneering method that employs deep learning within a probabilistic framework for the joint estimation of both direct and cascaded channels in an ambient backscatter (AmBC) network comprising multiple tags. In essence, we leverage an adversarial score-based generative model for training, enabling the acquisition of channel distributions. Subsequently, our channel estimation process involves sampling from the posterior distribution, facilitated by the annealed Langevin sampling technique. Notably, our method demonstrates substantial advancements over standard least square (LS) estimation techniques, achieving performance akin to that of the minimum mean square error (MMSE) estimator for the direct channel, and outperforming it for the cascaded channels.

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arXiv2023

Signal Detection in Ambient Backscatter Systems: Fundamentals, Methods, and Trends

Internet-of-Things (IoT) is rapidly growing in wireless technology, aiming to connect vast numbers of devices to gather and distribute vital information. Despite individual devices having low energy consumption, the cumulative demand results in significant energy usage. Consequently, the concept of ultra-low-power tags gains appeal. Such tags communicate by reflecting rather than generating the radio frequency (RF) signals by themselves. Thus, these backscatter tags can be low-cost and battery-free. The RF signals can be ambient sources such as wireless-fidelity (Wi-Fi), cellular, or television (TV) signals, or the system can generate them externally. Backscatter channel characteristics are different from conventional point-to-point or cooperative relay channels. These systems are also affected by a strong interference link between the RF source and the tag besides the direct and backscattering links, making signal detection challenging. This paper provides an overview of the fundamentals, challenges, and ongoing research in signal detection for AmBC networks. It delves into various detection methods, discussing their advantages and drawbacks. The paper's emphasis on signal detection sets it apart and positions it as a valuable resource for IoT and wireless communication professionals and researchers.

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arXiv2023

Time-Spread Pilot-Based Channel Estimation for Backscatter Networks

Current backscatter channel estimators employ an inefficient silent pilot transmission protocol, where tags alternate between silent and active states. To enhance performance, we propose a novel approach where tags remain active simultaneously throughout the entire training phase. This enables a one-shot estimation of both the direct and cascaded channels and accommodates various backscatter network configurations. We derive the conditions for optimal pilot sequences and also establish that the minimum variance unbiased (MVU) estimator attains the Cramer-Rao lower bound. Next, we propose new pilot designs to avoid pilot contamination. We then present several linear estimation methods, including least square (LS), scaled LS, and linear minimum mean square error (MMSE), to evaluate the performance of our proposed scheme. We also derive the analytical MMSE estimator using our proposed pilot designs. Furthermore, we adapt our method for cellular-based passive Internet-of-Things (IoT) networks with multiple tags and cellular users. Extensive numerical results and simulations are provided to validate the effectiveness of our approach. Notably, at least 10 dBm and 12 dBm power savings compared to the prior art are achieved when estimating the direct and cascaded channels. These findings underscore the practical benefits and superiority of our proposed technique.

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arXiv2023

Cell-Free Bistatic Backscatter Communication: Channel Estimation, Optimization, and Performance Analysis

This study introduces and investigates the integration of a cell-free architecture with bistatic backscatter communication (BiBC), referred to as cell-free BiBC or distributed access point (AP)-assisted BiBC, which can enable potential applications in future (EH)-based Internet-of-Things (IoT) networks. To that purpose, we first present a pilot-based channel estimation scheme for estimating the direct, cascaded, forward channels of the proposed system setup. We next utilize the channel estimates for designing the optimal beamforming weights at the APs, reflection coefficients at the tags, and reception filters at the reader to maximize the tag sum rate while meeting the tags' minimum energy requirements. Because the proposed maximization problem is non-convex, we propose a solution based on alternative optimization, fractional programming, and Rayleigh quotient techniques. We also quantify the computational complexity of the developed algorithms. Finally, we present extensive numerical results to validate the proposed channel estimation scheme and optimization framework, as well as the performance of the integration of these two technologies. Compared to the random beamforming/combining benchmark, our algorithm yields impressive gains. For example, it achieves $\sim$ 64.8\% and $\sim$ 253.5\% gains in harvested power and tag sum rate, respectively, for 10 dBm with 36 APs and 3 tags.

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arXiv2022

A Design of Low-Projection SCMA Codebooks for Ultra-Low Decoding Complexity in Downlink IoT Networks

This paper conceives a novel sparse code multiple access (SCMA) codebook design which is motivated by the strong need for providing ultra-low decoding complexity and good error performance in downlink Internet-of-things (IoT) networks, in which a massive number of low-end and low-cost IoT communication devices are served. By focusing on the typical Rician fading channels, we analyze the pair-wise probability of superimposed SCMA codewords and then deduce the design metrics for multi-dimensional constellation construction and sparse codebook optimization. For significant reduction of the decoding complexity, we advocate the key idea of projecting the multi-dimensional constellation elements to a few overlapped complex numbers in each dimension, called low projection (LP). An emerging modulation scheme, called golden angle modulation (GAM), is considered for multi-stage LP optimization, where the resultant multi-dimensional constellation is called LP-GAM. Our analysis and simulation results show the superiority of the proposed LP codebooks (LPCBs) including one-shot decoding convergence and excellent error rate performance. In particular, the proposed LPCBs lead to decoding complexity reduction by at least $97\%$ compared to that of the conventional codebooks, whilst owning large minimum Euclidean distance. Some examples of the proposed LPCBs are available at \url{https://github.com/ethanlq/SCMA-codebook}.

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arXiv2022

An Improved EPA based Receiver Design for Uplink LDPC Coded SCMA System

Sparse code multiple access (SCMA) is an emerging paradigm for efficient enabling of massive connectivity in future machine-type communications (MTC). In this letter, we conceive the uplink transmissions of the low-density parity check (LDPC) coded SCMA system. Traditional receiver design of LDPC-SCMA system, which is based on message passing algorithm (MPA) for multiuser detection followed by individual LDPC decoding, may suffer from the drawback of the high complexity and large decoding latency, especially when the system has large codebook size and/or high overloading factor. To address this problem, we introduce a novel receiver design by applying the expectation propagation algorithm (EPA) to the joint detection and decoding (JDD) involving an aggregated factor graph of LDPC code and sparse codebooks. Our numerical results demonstrate the superiority of the proposed EPA based JDD receiver over the conventional Turbo receiver in terms of both significantly lower complexity and faster convergence rate without noticeable error rate performance degradation.

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arXiv2019

Hybrid Codeword Position Index Modulation for Sparse Code Multiple Access System

In this paper, a novel variation of codeword position index based sparse code multiple access (CPI-SCMA) system, which is termed as hybrid codeword position index modulated sparse code multiple access (HCPI-SCMA), is proposed to further improve the transmission efficiency (TE). In this scheme, unlike the conventional CPI-SCMA that uses only one kind of bits-toindices (BTI) mapper, the codeword positions which are padded with zeros in CPI-SCMA are also utilized to transmit additional information. Since multiple index selectors are used in a HCPISCMA codeword, the original message passing algorithm (MPA) no longer works in HCPI-SCMA; hence, a modified MPA is proposed to detect the received signals. It is shown in the simulations and analysis that the proposed scheme can achieve both higher TE and better error rate performance in the region of high signal-to-noise ratio (SNR) compare to the conventional SCMA (C-SCMA). Moreover, compared with CPI-SCMA, HCPISCMA can achieve higher TE with approximately the same error rate performance compared to CPI-SCMA at high SNRs.

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arXiv2018

Codeword Position Index based Sparse Code Multiple Access System

In this letter, a novel variation of sparse code multiple access (SCMA), called codeword position index based SCMA (CPI-SCMA), is proposed. In this scheme, the information is transmitted not only by the codewords in M point SCMA codebook, but also by the indices of the codeword positions in a data block. As such, both the power and transmission efficiency (TE) can be improved, moreover, CPI-SCMA can achieve a better error rate performance compare to conventional SCMA (C-SCMA).

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arXiv2017

Spatial Resource Allocation for Spectrum Reuse in Unlicensed LTE Systems

In this paper, we study how to reuse the unlicensed spectrum in LTE-U systems while guaranteeing harmonious coexistence between the LTE-U and Wi-Fi systems. For a small cell with multiple antennas at the base station (SBS), some spatial degrees of freedom (DoFs) are used to serve small cell users (SUEs) while the rest are employed to mitigate the interference to the Wi-Fi users by applying zero-forcing beamforming (ZFBF). As a result, the LTE-U and Wi-Fi throughput can be balanced by carefully allocating the spatial DoFs. Due to the channel state information (CSI) estimation and feedback errors, ZFBF cannot eliminate the interference completely. We first analyze the residual interference among SUEs, called intra-RAT interference, and the interference to the Wi-Fi users, called inter-RAT interference after ZFBF, due to imperfect CSI. Based on the analysis, we derive the throughputs of the small cell and the Wi-Fi systems, respectively. Accordingly, a spatial DoF allocation scheme is proposed to balance the throughput between the small cell and the Wi-Fi systems. Our theoretical analysis and the proposed scheme are verified by simulation results.

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