| 1. |
- Ahmed, Mohammad Faisal, et al.
(författare)
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Privacy-Preserving Distributed Beamformer Design Techniques for Correlated Parameter Estimation
- 2023
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Ingår i: IEEE Sensors Journal. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1530-437X .- 1558-1748. ; 23:21, s. 26728-26739
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Tidskriftsartikel (refereegranskat)abstract
- Privacy-preserving distributed beamforming designs are conceived for temporally correlated vector parameter estimation in an orthogonal frequency division multiplexing (OFDM)-based wireless sensor network (WSN). The temporal correlation inherent in the parameter vector is exploited by the rate distortion theory-based bit allocation framework used for the optimal quantization of the sensor measurements. The proposed distributed beamforming designs are derived via fusion of the dual consensus alternating direction method of multiplier (DC-ADMM) technique with a pertinent privacy-preserving framework. This makes it possible for each sensor node (SN) to design its transmit precoders in a distributed fashion, which minimizes the susceptibility of vital information to malicious eavesdropper (Ev) nodes, while simultaneously avoiding the significant communication overhead required by a centralized approach for the transmission of the state information to the fusion center (FC). The Bayesian Cramer-Rao bound (BCRB) is derived for benchmarking the estimation performance of the proposed transmit beamformer and receiver combiner designs, while our simulation results illustrate the performance and explicitly demonstrate the trade-off between the privacy and estimation performance.
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| 2. |
- Clerckx, Bruno, et al.
(författare)
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Is NOMA Efficient in Multi-Antenna Networks? : A Critical Look at Next Generation Multiple Access Techniques
- 2021
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Ingår i: IEEE Open Journal of the Communications Society. - : Institute of Electrical and Electronics Engineers (IEEE). - 2644-125X. ; 2, s. 1310-1343
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Tidskriftsartikel (refereegranskat)abstract
- In the past few years, a large body of literature has been created on downlink Non-Orthogonal Multiple Access (NOMA), employing superposition coding and Successive Interference Cancellation (SIC), in multi-antenna wireless networks. Furthermore, the benefits of NOMA over Orthogonal Multiple Access (OMA) have been highlighted. In this paper, we take a critical and fresh look at the downlink Next Generation Multiple Access (NGMA) literature. Instead of contrasting NOMA with OMA, we contrast NOMA with two other multiple access baselines. The first is conventional Multi-User Linear Precoding (MU-LP), as used in Space-Division Multiple Access (SDMA) and multi-user Multiple-Input Multiple-Output (MIMO) in 4G and 5G. The second, called Rate-Splitting Multiple Access (RSMA), is based on multi-antenna Rate-Splitting (RS). It is also a non-orthogonal transmission strategy relying on SIC developed in the past few years in parallel and independently from NOMA. We show that there is some confusion about the benefits of NOMA, and we dispel the associated misconceptions. First, we highlight why NOMA is inefficient in multi-antenna settings based on basic multiplexing gain analysis. We stress that the issue lies in how the NOMA literature, originally developed for single-antenna setups, has been hastily applied to multi-antenna setups, resulting in a misuse of spatial dimensions and therefore loss in multiplexing gains and rate. Second, we show that NOMA incurs a severe multiplexing gain loss despite an increased receiver complexity due to an inefficient use of SIC receivers. Third, we emphasize that much of the merits of NOMA are due to the constant comparison to OMA instead of comparing it to MU-LP and RS baselines. We then expose the pivotal design constraint that multi-antenna NOMA requires one user to fully decode the messages of the other users. This design constraint is responsible for the multiplexing gain erosion, rate and spectral efficiency loss, ineffectiveness to serve a large number of users, and inefficient use of SIC receivers in multi-antenna settings. Our analysis and simulation results confirm that NOMA should not be applied blindly to multi-antenna settings, highlight the scenarios where MU-LP outperforms NOMA and vice versa, and demonstrate the inefficiency, performance loss, and complexity disadvantages of NOMA compared to RSMA. The first takeaway message is that, while NOMA is suited for single-antenna settings (as originally intended), it is not efficient in most multi-antenna deployments. The second takeaway message is that another non-orthogonal transmission framework, based on RSMA, exists which fully exploits the multiplexing gain and the benefits of SIC to boost the rate and the number of users to serve in multi-antenna settings and outperforms both NOMA and MU-LP. Indeed, RSMA achieves higher multiplexing gains and rates, serves a larger number of users, is more robust to user deployments, network loads and inaccurate channel state information and has a lower receiver complexity than NOMA. Consequently, RSMA is a promising technology for NGMA and future networks such as 6G and beyond.
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| 3. |
- Dutta, Amit Kumar, et al.
(författare)
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Minimum-Error-Probability CFO Estimation for Multiuser MIMO-OFDM Systems
- 2015
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Ingår i: IEEE Transactions on Vehicular Technology. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9545 .- 1939-9359. ; 64:7, s. 2804-2818
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Tidskriftsartikel (refereegranskat)abstract
- We consider carrier frequency offset (CFO) estimation in the context of multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems over noisy frequency-selective wireless channels with both single- and multiuser scenarios. We conceived a new approach for parameter estimation by discretizing the continuous-valued CFO parameter into a discrete set of bins and then invoked detection theory, analogous to the minimum-bit-error-ratio optimization framework for detecting the finite-alphabet received signal. Using this radical approach, we propose a novel CFO estimation method and study its performance using both analytical results and Monte Carlo simulations. We obtain expressions for the variance of the CFO estimation error and the resultant BER degradation with the single- user scenario. Our simulations demonstrate that the overall BER performance of a MIMO-OFDM system using the proposed method is substantially improved for all the modulation schemes considered, albeit this is achieved at increased complexity.
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| 4. |
- Hoang, Tiep M., et al.
(författare)
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Detection of Spoofing Attacks in Aeronautical Ad-hoc Networks Using Deep Autoencoders
- 2022
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Ingår i: IEEE Transactions on Information Forensics and Security. - : Institute of Electrical and Electronics Engineers (IEEE). - 1556-6013 .- 1556-6021. ; 17, s. 1010-1023
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Tidskriftsartikel (refereegranskat)abstract
- We consider an aeronautical ad-hoc network relying on aeroplanes operating in the presence of a spoofer. The aggregated signal received by the terrestrial base station is considered as 'clean' or 'normal', if the legitimate aeroplanes transmit their signals and there is no spoofing attack. By contrast, the received signal is considered as 'spurious' or 'abnormal' in the face of a spoofing signal. An autoencoder (AE) is trained to learn the characteristics/features from a training dataset, which contains only normal samples associated with no spoofing attacks. The AE takes original samples as its input samples and reconstructs them at its output. Based on the trained AE, we define the detection thresholds of our spoofing discovery algorithm. To be more specific, contrasting the output of the AE against its input will provide us with a measure of geometric waveform similarity/dissimilarity in terms of the peaks of curves. To quantify the similarity between unknown testing samples and the given training samples (including normal samples), we first propose a so-called deviation-based algorithm. Furthermore, we estimate the angle of arrival (AoA) from each legitimate aeroplane and propose a so-called AoA-based algorithm. Then based on a sophisticated amalgamation of these two algorithms, we form our final detection algorithm for distinguishing the spurious abnormal samples from normal samples under a strict testing condition. In conclusion, our numerical results show that the AE improves the trade-off between the correct spoofing detection rate and the false alarm rate as long as the detection thresholds are carefully selected.
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| 5. |
- Jafri, Meesam, et al.
(författare)
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Cooperative Hybrid Transmit Beamforming in Cell-free mmWave MIMO Networks
- 2023
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Ingår i: IEEE Transactions on Vehicular Technology. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9545 .- 1939-9359. ; 72:5, s. 6023-6038
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Tidskriftsartikel (refereegranskat)abstract
- Hybrid precoders and combiners are designed for cooperative cell-free multi-user millimeter wave (mmWave) multiple-input multiple-output (MIMO) cellular networks for low complexity interference mitigation. Initially, we derive an optimal hybrid transmit beamformer (HTBF) for a broadcast scenario considering both total and per access point (AP) power constraints. Next, an optimal successive hybrid beamformer technique is proposed for unicast and multicast scenarios which relies on the optimal minimum variance distortionless response (MVDR). We demonstrate that it mitigates both the interuser and intergroup interference, while successively ensuring orthogonality to the previously scheduled users/user groups. Furthermore, it is shown theoretically that the proposed schemes are capable of supporting a large number of users. Subsequently, a Bayesian learning (BL) based method is conceived for jointly designing the RF and baseband precoders/combiners for the various scenarios considered. Furthermore, we also conceive the uplink counterpart of our HTBF scheme, which is based on maximizing the signal-to-interference-plus noise ratio (SINR) of each individual user. Finally, the efficacy of the proposed schemes is characterized by our extensive simulation results in terms of cancelling the interuser/intergroup interference, which improves the spectral efficiency.
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| 6. |
- Maity, Priyanka, et al.
(författare)
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Hybrid Precoder and Combiner Designs for Decentralized Parameter Estimation in mmWave MIMO Wireless Sensor Networks
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 11:1, s. 1629-1643
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Tidskriftsartikel (refereegranskat)abstract
- Hybrid precoder and combiner designs are conceived for decentralized parameter estimation in millimeter wave (mmWave) multiple-input-multiple-output (MIMO) wireless sensor networks (WSNs). More explicitly, efficient pre- and post-processing of the sensor observations and received signal are proposed for the minimum mean square error (MMSE) estimation of a parameter vector. The proposed techniques exploit the limited scattering nature of the mmWave MIMO channel for formulating the hybrid transceiver design framework as a multiple measurement vectors (MMVs)-based sparse signal recovery problem. This is then solved using the iterative appealingly low-complexity simultaneous orthogonal matching pursuit (SOMP). Tailor-made designs are presented for WSNs operating under both total and per-sensor power constraints, while considering ideal noiseless as well as realistic noisy sensors. Furthermore, both the Bayesian Cramer-Rao lower bound and the centralized MMSE bound are derived for benchmarking the proposed decentralized estimation schemes. Our simulation results demonstrate the efficiency of the designs advocated and verify the analytical findings.
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| 7. |
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| 8. |
- Rajput, Kunwar Pritiraj, et al.
(författare)
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Robust Decentralized and Distributed Estimation of a Correlated Parameter Vector in MIMO-OFDM Wireless Sensor Networks
- 2021
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Ingår i: IEEE Transactions on Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 0090-6778 .- 1558-0857. ; 69:10, s. 6894-6908
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Tidskriftsartikel (refereegranskat)abstract
- An optimal precoder design is conceived for the decentralized estimation of an unknown spatially as well as temporally correlated parameter vector in a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) based wireless sensor network (WSN). Furthermore, exploiting the temporal correlation present in the parameter vector, a rate-distortion theory based framework is developed for the optimal quantization of the sensor observations so that the resultant distortion is minimized for a given bit-budget. Subsequently, optimal precoders are also developed that minimize the sum-MSE (SMSE) for the scenario of transmitting quantized observations. In order to reduce the computational complexity of the decentralized framework, distributed precoder design algorithms are also developed which design precoders using the consensus based alternating direction method of multipliers (ADMM), wherein each SN determines its precoders without any central coordination by the fusion center. Finally, new robust MIMO precoder designs are proposed for practical scenarios operating in the face of channel state information (CSI) uncertainty. Our simulation results demonstrate the improved performance of the proposed schemes and corroborate our analytical formulations.
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| 9. |
- Rajput, Kunwar Pritiraj, et al.
(författare)
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Robust Finite-Resolution Transceivers for Decentralized Estimation in Energy-Harvesting-Aided IoT Networks
- 2023
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Ingår i: IEEE Sensors Journal. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1530-437X .- 1558-1748. ; 23:22, s. 28191-28204
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Tidskriftsartikel (refereegranskat)abstract
- This article develops novel approaches for designing robust transceivers and energy covariance in an IoT network (IoTNe) powered by energy harvesting (EH). Our goal is to minimize the mean square error (mse) at the fusion center (FC) while considering the uncertainty of channel state information (CSI). The proposed designs incorporate both Gaussian and bounded CSI uncertainty models to model the uncertainty in CSI. Furthermore, two different optimal bit allocation schemes have been proposed for quantizing the measurements from each sensor node (SeN). However, solving the resulting mse optimization problems with constraints on individual SeN power and total bit rate proves to be challenging due to their nonconvex nature under both CSI uncertainty models. To address this challenge, we develop a block coordinate descent (BCD)-based iterative framework. This framework leverages the block convexity of the optimization objective and provides efficient solutions for both uncertainty paradigms considered. By making use of this analytical tractability, we obtain improved performance compared with the uncertainty-agnostic scheme that disregards CSI uncertainty. We validate our approach through numerical simulations, which not only support our analytical findings but also demonstrate the superior performance achieved with our method that accounts for CSI uncertainty.
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| 10. |
- Rajput, Kunwar Pritiraj, et al.
(författare)
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Robust Linear Hybrid Beamforming Designs Relying on Imperfect CSI in mmWave MIMO IoT Networks
- 2023
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Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662 .- 2372-2541. ; 10:10, s. 8893-8906
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Tidskriftsartikel (refereegranskat)abstract
- Linear hybrid beamformer designs are conceived for the decentralized estimation of a vector parameter in a millimeter wave (mmWave) multiple-input multiple-output (MIMO) Internet of Things network (IoTNe). The proposed designs incorporate both total IoTNe and individual IoTNo power constraints, while also eliminating the need for a baseband receiver combiner at the fusion center (FC). To circumvent the non-convexity of the hybrid beamformer design problem, the proposed approach initially determines the minimum mean square error (MMSE) digital transmit precoder (TPC) weights followed by a simultaneous orthogonal matching pursuit (SOMP)-based framework for obtaining the analog RF and digital baseband TPCs. Robust hybrid beamformers are also derived for the realistic imperfect channel state information (CSI) scenario, utilizing both the stochastic and norm-ball CSI uncertainty frameworks. The centralized MMSE bound derived in this work serves as a lower bound for the estimation performance of the proposed hybrid TPC designs. Finally, our simulation results quantify the benefits of the various designs developed.
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