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This paper studies the eigenvalue decomposition (EVD) based uplink channel estimation in multi-cell massive multi-input multi-output (MIMO) networks. The performance of the conventional EVD-based channel estimators is limited by the interference from other users in the network due to finite number of antennas and finite transmit samples. We propose an iterative optimization procedure with multiple...
Rating Prediction is a key problem in recommendation system, especially in Bigdata environment with data sparsity. Recently, Factorization Machine (FM) has been proven to be effective in solving the recommendation problem. Whereas, valuable category information of users and items are neglected in basic FM model. In this paper, we fully explore the capabilities of category information to improve the...
In this paper, a sectorized multi-cell massive multiple-input multiple-output (MIMO) system is considered with a spatially correlated channel model. Since sum-throughput per cell is an important index for evaluating a multi-cell system, we derive the ergodic achievable uplink sum-throughput per cell of the sectorized system and give the deterministic approximation of it based on the large random matrix...
In this work, a Behaviour-based Intrusion Detection Model is suggested. The proposed model can be employed from a single host configuration to a distributed mixture of host-based and network-based Intrusion Detection Systems (IDSs). Unlike most state-of-the-art IDSs that rely on analysing lower-level, raw-data representations, our proposed architecture suggests to use higher-level notions -behaviours-...
Massive multiple input multiple output (MIMO) millimeter wave (MMW) communications allow for a compact implementation and efficient beamforming. In this paper we focus on the problem of estimating the massive MIMO channel in a code modulated path sharing multi-antenna (CPMA) architecture, when a limited number of radio frequency (RF) chains is available, and beamforming is performed through a combination...
We consider channel estimation for massive multiple-input multiple-output (MIMO) systems operating in frequency division duplexing (FDD) mode. By exploiting the sparsity of significant propagation paths in massive MIMO channels, we develop a compressed sensing (CS) based channel estimator that can reduce the pilot overhead as compared with the conventional least squares (LS) and minimum mean square...
In this study, a series of experiments were conducted to examine the feasibility of using Wi-Fi signals for gesture recognition in indoor environments. Totally different from traditional sensor-based approach and computer vision approach, the proposed novel gesture recognition method does not require line-of-sight and sensors placed in the body. Furthermore, unlike recent work using Doppler shifts...
This paper presents an application of cognitive networking paradigm to the problem of inter-cell interference coordination (ICIC) in Long-Term Evolution-Uplink (LTE-UL). We describe state-of-the-art, research challenges involved, and a novel random neural network (RNN) based power controller and interference management framework. The RNN based cognitive engine (CE) learns how the electromagnetic environment...
Cognitive radio is regarded as the most promising technology for driving the future development of next-generation wireless networks, increasing spectrum efficiency by dynamic spectrum access. Allowing white spaces to be used in a deregulated manner exposes the radio spectrum to anomalous usage, which in turn may intentionally or unintentionally cause interference to primary users (PUs) as well as...
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