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This study investigates the outage performance of an under-laying wireless-powered secondary system that reuses the primary users (PU) spectrum in a multiple-input multiple-output (MIMO) cognitive radio (CR) network. Each secondary user…

Information Theory · Computer Science 2023-09-19 Iman Pazouki , Roshanak Soltani , Mohammad Lari

This work examines a novel heterogeneous dynamic spectrum access network where the primary users (PUs) coexist with both underlay and interweave cognitive radios (ICRs); all terminals being potentially equipped with multiple antennas.…

Information Theory · Computer Science 2012-06-08 Amitav Mukherjee , A. Lee Swindlehurst

Multi-scale spectrum sensing is proposed to overcome the cost of full network state information on the spectrum occupancy of primary users (PUs) in dense multi-cell cognitive networks. Secondary users (SUs) estimate the local spectrum…

Information Theory · Computer Science 2018-12-07 Nicolo Michelusi , Matthew Nokleby , Urbashi Mitra , Robert Calderbank

This study describes a binaural machine hearing system that is capable of performing auditory stream segregation in scenarios where multiple sound sources are present. The process of stream segregation refers to the capability of human…

Sound · Computer Science 2016-06-27 Christopher Schymura , Thomas Walther , Dorothea Kolossa

This paper considers a cooperative OFDMA-based cognitive radio network where the primary system leases some of its subchannels to the secondary system for a fraction of time in exchange for the secondary users (SUs) assisting the…

Information Theory · Computer Science 2012-09-17 Meixia Tao , Yuan Liu

Positive-Unlabeled (PU) learning tries to learn binary classifiers from a few labeled positive examples with many unlabeled ones. Compared with ordinary semi-supervised learning, this task is much more challenging due to the absence of any…

Machine Learning · Computer Science 2022-12-07 Yunrui Zhao , Qianqian Xu , Yangbangyan Jiang , Peisong Wen , Qingming Huang

Positive-Unlabeled (PU) learning aims to learn a model with rare positive samples and abundant unlabeled samples. Compared with classical binary classification, the task of PU learning is much more challenging due to the existence of many…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Chengming Xu , Chen Liu , Siqian Yang , Yabiao Wang , Shijie Zhang , Lijie Jia , Yanwei Fu

The spectrum sharing has recently passed into a mainstream Cognitive Radio (CR) strategy. We investigate the core issue in this strategy: interference mitigation at Primary Receiver (PR).We propose a linear precoder design which aims at…

Networking and Internet Architecture · Computer Science 2012-08-28 Abdelwaheb Marzouki , Xin Jin

We investigate the coexistence of underlay spectrum sharing in cell-free massive multiple-input multiple-output (MIMO) systems. A primary system with geographically distributed primary access points (P-APs) serves a multitude of primary…

Information Theory · Computer Science 2021-04-21 Diluka Loku Galappaththige , Gayan Amarasuriya Aruma Baduge

Cognitive Radio (CR) aims to increase the spectrum utilization by allowing secondary users (SU) to access unused licensed spectrum bands. To maximize the throughput given limited sensing capability, SUs need to strike a balance between…

Networking and Internet Architecture · Computer Science 2012-01-24 Yuan Lu , Alexandra Duel-Hallen

In this paper, the performance of an underlay multiple-input multiple-output (MIMO) cognitive radio system is analytically studied. In particular, the secondary transmitter operates in a spatial multiplexing transmission mode, while a…

Information Theory · Computer Science 2017-12-05 Nikolaos I. Miridakis , Minghua Xia , Theodoros A. Tsiftsis

Certain applications require the use of signals that combine both the capability to operate with low signal-to-noise ratios and the ability to support multiple users without interference. In the case where many users have very different…

Information Theory · Computer Science 2021-03-10 Patricio G. Donato , Matias N. Hadad , Marcos A. Funes

Blind source separation is a research hotspot in the field of signal processing because it aims to separate unknown source signals from observed mixtures through an unknown transmission channel. A low computational complexity instantaneous…

Signal Processing · Electrical Eng. & Systems 2019-03-08 Pengfei Xu , Yinjie Jia , Zhijian Wang

Stochastic binary hidden units in a multi-layer perceptron (MLP) network give at least three potential benefits when compared to deterministic MLP networks. (1) They allow to learn one-to-many type of mappings. (2) They can be used in…

Machine Learning · Statistics 2015-04-10 Tapani Raiko , Mathias Berglund , Guillaume Alain , Laurent Dinh

In the conventional multiuser MIMO systems, user selection and scheduling has previously been used as an effective way to increase the sum rate performance of the system. However, the recent concepts of the massive MIMO systems (at…

Information Theory · Computer Science 2016-11-29 Waqas Ahmad , Geamel Alyami , Ivica Kostanic

A distributed binary hypothesis testing problem is studied with one observer and two decision centers. Achievable type-II error exponents are derived for testing against conditional independence when the observer communicates with the two…

Information Theory · Computer Science 2020-01-24 Sadaf Salehkalaibar , Michele Wigger , Roy Timo

We consider binary continuous phase modulation (CPM) signals used in some recent low-cost and low-power consumption telecommunications standard. When these signals are generated through a low-cost transmitter, the real modulation index can…

Information Theory · Computer Science 2015-09-14 Malek Messai , Colavolpe Giulio , Amis Karine , Guilloud Frederic

We employ Permutation Trellis Code (PTC) based multi-level Frequency Shift Keying signaling to mitigate the impact of Primary Users (PUs) on the performance of Secondary Users (SUs) in Cognitive Radio Networks (CRNs). The PUs are assumed to…

Information Theory · Computer Science 2014-12-15 Raghed El-Bardan , Engin Masazade , Onur Ozdemir , Yunghsiang S. Han , Pramod K. Varshney

We propose a neural network model that can separate target speech sources from interfering sources at different angular regions using two microphones. The model is trained with simulated room impulse responses (RIRs) using omni-directional…

Audio and Speech Processing · Electrical Eng. & Systems 2024-01-18 Yang Yang , George Sung , Shao-Fu Shih , Hakan Erdogan , Chehung Lee , Matthias Grundmann

Binary neural networks improve computationally efficiency of deep models with a large margin. However, there is still a performance gap between a successful full-precision training and binary training. We bring some insights about why this…

Machine Learning · Computer Science 2020-04-22 Xinlin Li , Vahid Partovi Nia