September 2020
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55 Reads
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5 Citations
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Publications (106)
April 2020
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14 Reads
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2 Citations
IEEE Transactions on Green Communications and Networking
This paper addresses the problem of centralized transceiver design for multiuser MIMO amplify-and-forward (AF) relaying within a cloud radio access network (C-RAN). The aim is to optimize AF matrices of remote radio heads (RRHs) acting as relays, in order to improve the reception quality at the destinations while reducing network power consumption and feedback overhead on the fronthaul links. A two-stage method is proposed to solve this problem efficiently. The first stage relies on interference leakage minimization subject to per-relay transmit power constraints along with signal preserving constraints. To reduce the total network power, RRH selection is achieved by incorporating in the objective function a regularization term that promotes group-sparsity among the RRHs. In the second stage, to reduce feedback overhead, a different penalty term is added that induces weight-level sparsity in the AF matrix of each active RRH. For both stages, low-complexity iterative algorithms based on the alternating direction method of multipliers (ADMM) are developed to solve the corresponding regularized problems with low complexity. Extensive simulations are performed to demonstrate the explicit benefits of the proposed design method, which results in notably lower power consumption, computational complexity and weight feedback overhead than conventional approaches.
![Detection performance in K‐distributed clutter α=0.1,δ∼U(0,1],J=16,L2=64](https://www.researchgate.net/profile/Ahmed-Abouelfadl/publication/335164025/figure/fig5/AS:11431281179110261@1691154490020/Detection-performance-in-K-distributed-clutter-a01-dU0-1-J16-L264_Q320.jpg)
November 2019
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117 Reads
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10 Citations
Space time adaptive processing (STAP) detects targets by computing adaptive weight vectors for each cell under test using its covariance matrix, as estimated from surrounding secondary cells. In this context, the non-homogeneity detector (NHD) excludes the anomalous secondary cells that adversely affect the detection performance. The existing robust NHDs require estimating the covariance matrix of each secondary cell, which hinders their implementation in modern radars with large-dimensional range cells. In this paper, we propose a new low-complexity NHD that is suitable for highly correlated clutter environments with both Gaussian and non-Gaussian heavy-tailed distributions. The proposed detector, which is based on the projection depth function from the field of robust statistics, features a nonparametric and covariance-free test statistic. As a result, its computational complexity is much lower than that of current NHDs, such as the widely used normalized adaptive matched filter (NAMF) detector, especially for large-dimensional range cells. In Monte Carlo simulations with different clutter distributions and radar system configurations, the proposed detector shows a comparable performance to that of NAMF. The low complexity and robust performance of the new detector make it particularly attractive for real time applications.
November 2019
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37 Reads
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1 Citation
September 2019
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34 Reads
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2 Citations
September 2019
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9 Reads
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3 Citations
December 2018
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18 Reads
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5 Citations
August 2018
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14 Reads
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1 Citation
July 2018
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43 Reads
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4 Citations
January 2018
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433 Reads
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1 Citation
It is inconceivable how chaotic the world would look to humans, faced with innumerable decisions a day to be made under uncertainty, had they been lacking the capacity to distinguish the relevant from the irrelevant---a capacity which computationally amounts to handling probabilistic independence relations. The highly parallel and distributed computational machinery of the brain suggests that a satisfying process-level account of human independence judgment should also mimic these features. In this work, we present the first rational, distributed, message-passing, process-level account of independence judgment, called . Interestingly, shows a curious, but normatively-justified tendency for quick detection of dependencies, whenever they hold. Furthermore, outperforms all the previously proposed algorithms in the AI literature in terms of worst-case running time, and a salient aspect of it is supported by recent work in neuroscience investigating possible implementations of Bayes nets at the neural level. nicely exemplifies how the pursuit of cognitive plausibility can lead to the discovery of state-of-the-art algorithms with appealing properties, and its simplicity makes potentially a good candidate for pedagogical purposes.
Citations (50)
... To find the elements of the FIM Υ, we need to calculate the second order partial derivatives (hessian matrix) of the loglikelihood function L(θ) with respect to each of the channel parameters θ as shown in (40), and take the expectation with respect to the corresponding noise tensor unfoldings. With (36) and (37), the partial derivatives of L(θ) in (38) and (39) with respect to a single channel parameter are: ...
- Citing Conference Paper
October 2024
... However, in the face of this challenge, emergency responders obtain near-instantaneous access to critical information by linking next-generation sensors, HAR algorithms, and immersive virtual environments in the Metaverse [12,92]. The continuous flow of real-time environmental sensor data can detect structural failures or accelerating rises in floodwater to HAR systems, identifying individuals who have fallen or are showing signs of physical distress. ...
- Citing Article
- Full-text available
January 2024
IEEE Open Journal of the Communications Society
... This is an important issue to highlight as improving communication through FD transmission requires knowledge of estimating both the RIS assisted channels and the non-RIS assisted channels: the direct-path between the AP and UE or the self-interference at the AP and UE. However, having separate channel estimation stages where the RIS is turned "off" then "on" leads to extra pilot overhead compared to jointly estimating all channels with what the least squares solution provides in [38], [39] for HD and [16] for FD scenarios. ...
- Citing Article
October 2023
IEEE Wireless Communications Letters
... Under the strict delay requirements, the system's energy consumption is minimized by optimizing resource allocation and sub-channel allocation. In [20], the author studied the device-to-device (D2D) assisted fog computing scenario in minimizing the system's energy consumption under the probabilistic constraint of task processing time. The above researches are to reduce the system's energy consumption through different optimization methods in various application scenarios. ...
- Citing Conference Paper
December 2021
... Energy utilization is the total energy consumed by end-user IoT devices, the Fog computing layer, and the Cloud computing layer for executing and transmitting user-generated requests [29,35]. This article determines the total energy consumption of the framework as the aggregate of: (I) the energy expended by the end-user IoT gadget layer for transmitting any request to either the Fog computing layer or the Cloud computing layer via communication devices ...
- Citing Article
December 2022
IEEE Transactions on Green Communications and Networking
... As reported in [10], an universal pulse-based joint estimation algorithm of clock skew and offset in WSNs is introduced with the propagation delay estimated under a reference clock. In addition, typical pulse-based synchronization methods without reference clock are presented in [11][12][13]. The clock offset estimation methods are given in [11] and [12] with assuming the ideal condition that takes neither propagation delay nor clock skew into account. ...
- Citing Article
- Full-text available
January 2021
IEEE Open Journal of the Communications Society
... The spatial diversity in MIMO radars brings several advantages, including improvement of spatial resolution, parameter estimation accuracy, ground moving target identification, and detection performance [1]. For extended target models, where the target occupies several range cells [2], the so-called cognitive MIMO radars, adapt the transmitted waveforms to the target impulse response (TIR) to improve target detection [3]. ...
- Citing Conference Paper
- Full-text available
November 2019
... Pulse-based synchronization is typically implemented by distributed phase locked-loops (DPLL) [16], [17]. The performance of DPLL is affected by the duplexing scheme employed by the devices. ...
- Citing Conference Paper
September 2019
... In our previous work [30], we proposed the Wavelet Subband Decomposition (WSD) structure that decomposes an input image using wavelets and then processes each of the resulting subbands using separate convolutional layers whose outputs are combined by a fully connected (FC) layer. As we discuss in [30], the network exhibits several attractive properties such as structural regularization, immunity from input and weight quantization noise, etc. ...
- Citing Conference Paper
September 2019
... The second is the Kdistribution which, although encountered in real applications [47], has been scarcely explored in the literature. In both cases, the TIR between each pair of the transmitting and receiving antenna elements is generated as a spherical invariant random vector (SIRV) [48], [49] which is assumed to be known by the radar system as in [10], [11], [21]. For a comprehensive evaluation of the proposed method, we use K = 1000 Monte Carlo simulation trials, each with a different TIR for both considered TIR distributions and antenna sizes. ...
- Citing Article
- Full-text available
November 2019