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The performance of conventional interference management strategies degrades when interference power is comparable to signal power. We consider a new perspective on interference management using semantic communication. Specifically, a…

Signal Processing · Electrical Eng. & Systems 2024-08-09 Zian Meng , Qiang Li , Ashish Pandharipande , Xiaohu Ge

In this paper, we introduce a new algorithm to deal with the stalling effect in the LMS algorithm used in adaptive filters. We modify the update rule of the tap weight vectors by adding noise, generated by a noise generator. The properties…

Signal Processing · Electrical Eng. & Systems 2018-07-20 Hamid Reza Shahdoosti

In diffusion-based algorithms for adaptive distributed estimation, each node of an adaptive network estimates a target parameter vector by creating an intermediate estimate and then combining the intermediate estimates available within its…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-12-08 Reza Arablouei , Stefan Werner , Kutluyıl Doğançay , Yih-Fang Huang

We study the performance of centralized least mean-squares (CLMS) algorithms in wireless sensor networks where nodes transmit their data over fading channels to a central processing unit (e.g., fusion center or cluster head), for parameter…

Systems and Control · Computer Science 2016-11-18 Reza Abdolee , Benoit Champagne

We identify phase noise as a bottleneck for the performance of digital self-interference cancellers that utilize a single auxiliary receiver---single-tap digital cancellers---and operate in multipath propagation environments. Our analysis…

Information Theory · Computer Science 2017-06-30 Paul Ferrand , Melissa Duarte

In cellular Orthogonal Frequency Division Multiplexing (OFDM) networks, Co-Channel Interference (CCI) leads to severe degradation in the BER performance. To solve this problem, Maximum-Likelihood Estimation (MLE) CCI cancellation scheme has…

Information Theory · Computer Science 2009-12-10 Manar Mohaisen , KyungHi Chang

To estimate multiple-input multiple-output (MIMO) channels, invariable step-size normalized least mean square (ISSNLMS) algorithm was applied to adaptive channel estimation (ACE). Since the MIMO channel is often described by sparse channel…

Information Theory · Computer Science 2013-11-07 Guan Gui , Shinya kumagai , Fumiyuki Adachi

This paper presents adaptive bidirectional minimum mean-square error parameter estimation algorithms for fast-fading channels. The time correlation between successive channel gains is exploited to improve the estimation and tracking…

Information Theory · Computer Science 2015-10-14 P. Clarke , R. C. de Lamare

The necessity of accurate channel estimation for Successive and Parallel Interference Cancellation is well known. Iterative channel estimation and channel decoding (for instance by means of the Expectation-Maximization algorithm) is…

Information Theory · Computer Science 2016-11-17 Francisco Lazaro Blasco , Francesco Rossetto

Phase noise (PN) is a major disturbance in MIMO systems, where the contribution of different oscillators at the transmitter and the receiver side may degrade the overall performance and offset the gains offered by MIMO techniques. This is…

Information Theory · Computer Science 2024-05-14 Alberto Tarable , Francisco J. Escribano

Accurate channel estimation is essential for broadband wireless communications. As wireless channels often exhibit sparse structure, the adaptive sparse channel estimation algorithms based on normalized least mean square (NLMS) have been…

Information Theory · Computer Science 2013-11-07 Guan Gui , Linglong Dai , Shinya Kumagai , Fumiyuki Adachi

The classical iteratively reweighted least-squares (IRLS) algorithm aims to recover an unknown signal from linear measurements by performing a sequence of weighted least squares problems, where the weights are recursively updated at each…

Machine Learning · Statistics 2024-06-06 Chiraag Kaushik , Justin Romberg , Vidya Muthukumar

Channel estimation problem is one of the key technical issues in time-variant multiple-input single-output (MSIO) communication systems. To estimate the MISO channel, least mean square (LMS) algorithm is applied to adaptive channel…

Information Theory · Computer Science 2013-02-07 Guan Gui , Wei Peng , Abolfazl Mehbodniya , Fumiyuki Adachi

The proportionate normalized least mean square (PNLMS) algorithm and its variants are by far the most popular adaptive filters that are used to identify sparse systems. The convergence speed of the PNLMS algorithm, though very high…

Information Theory · Computer Science 2015-07-13 Rajib Lochan Das , Mrityunjoy Chackraborty

Communications in dispersive direct-sequence code-division multiple-access (DS-CDMA) channels suffer from intersymbol and multiple-access interference, which can significantly impair performance. Joint maximum \textit{a posteriori}…

Information Theory · Computer Science 2007-07-13 Husheng Li , H. V. Poor

Noise cancellation is one of the important signal processing functions of any communication system, as noise affects data integrity. In existing systems, traditional filters are used to cancel the noise from the received signals. These…

Signal Processing · Electrical Eng. & Systems 2018-01-31 Adnan Quadri , Mohsen Riahi Manesh , Naima Kaabouch

We propose a parallel constructive interference (CI)-based symbol-level precoding (SLP) approach for massive connectivity in the downlink of multiuser multiple-input single-output (MU-MISO) systems, with only local channel state information…

Information Theory · Computer Science 2022-09-27 Junwen Yang , Ang Li , Xuewen Liao , Christos Masouros

When the input signal is correlated input signals, and the input and output signal is contaminated by Gaussian noise, the total least squares normalized subband adaptive filter (TLS-NSAF) algorithm shows good performance. However, when it…

Signal Processing · Electrical Eng. & Systems 2023-07-21 Haiquan Zhao , Zian Cao , Yida Chen

Broadband wireless channels usually have the sparse nature. Based on the assumption of Gaussian noise model, adaptive filtering algorithms for reconstruction sparse channels were proposed to take advantage of channel sparsity. However,…

Information Theory · Computer Science 2015-02-20 Guan Gui , Li Xu , Wentao Ma , Badong Chen

In optical transport networks, signal lightpaths between two terminal nodes can be different due to current network conditions. Thus the transmission distance and accumulated dispersion in the lightpath cannot be predicted. Therefore, the…

Information Theory · Computer Science 2018-05-09 Tianhua Xu , Gunnar Jacobsen , Jie Li , Mark Leeson , Sergei Popov