Channel capacity of multiple‐input multiple‐output ultra‐wideband systems with single co‐channel interference

Liao, Shu‐Han; Chiu, Chien‐Ching; Ho, Min-Hui; Liu, Chunliang

doi:10.1002/dac.1131

Cited by 21 publications

(16 citation statements)

References 16 publications

(10 reference statements)

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“…1, and the received signal is described as follows: B. Channel modeling By using these images and received fields, the channel frequency response can be obtained as following [7][8][9][10][11][12][13][14] …”

Section: A System Descriptionmentioning

confidence: 99%

Comparison of different antenna arrays for the channel capacity

Liao

Chen²,

Chiu

et al. 2015

2015 International Conference on Computing, Communication and Security (ICCCS)

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Section: A System Descriptionmentioning

confidence: 99%

Comparison of different antenna arrays for the channel capacity

Liao

Chen²,

Chiu

et al. 2015

2015 International Conference on Computing, Communication and Security (ICCCS)

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“…However, the open feature of the wireless channels makes the wireless communication systems prone to man-made interference, which can be classified into two different types: unintended and intended [1,2]. However, the open feature of the wireless channels makes the wireless communication systems prone to man-made interference, which can be classified into two different types: unintended and intended [1,2].…”

Section: Introductionmentioning

confidence: 99%

A blind signal‐to‐jamming‐plus‐noise ratio estimation based on second‐order cyclostationarity under typical tone‐jamming and its CRLB

Yao¹,

Gao

Niu³

et al. 2016

Int J Communication

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In this paper, a blind signal-to-jamming-plus-noise ratio (SJNR) estimation under typical tone-jamming is proposed in a Rayleigh fading channel. Based on the differences among communication signal, jamming, and noise in cyclostationarity, the proposed algorithm obtained SJNR values by using different parts of the cyclic autocorrelation matrix of received signals and applying the minimum square error (MSE) method to estimate the communication signal power and jamming-plus-noise power, respectively. Through deriving the Cramer-Rao lower bound (CRLB) for the SJNR estimation, the normalized MSE performance is examined. Simulation results show that the proposed estimation performs better than the subspace-based eigenvalue decomposition estimation on a normalized estimation bias, and its normalized MSE performance is also closer to CRLB. absence of jamming. These provide the needed channel quality information for many adaptive technologies, such as power control [9,10], transmission rate adaption [11], handoff [12], and channel allocation control [13].Signal-to-noise ratio and SINR estimations are generally divided into two categories: non-blind estimation method, also known as data-aided method, which sends periodic training sequence or pilot frequency sequence, and thus to estimate the SNR and SINR. Blind estimation method, that is, non-data-aided method does not send the training sequence or secondary data but estimate them only by characteristics of communication signals. The complexity of non-blind estimation is lower with better real-time, but it certainly occupies part of the effective bandwidth and reduce transmission efficiency while sending training sequence. Blind estimation method does not take up communication spectrum, its transmission efficiency is higher, but usually the estimation complexity is also higher, and it requires longer data sequence, the real-time is poor, and the accuracy is slightly worse. Non-blind estimation is the main application of the existing communication system, but to improve the transmission efficiency of the system, the research on blind estimation algorithm is more active. The existing SNR estimations mainly include maximum likelihood (ML) criterionbased estimations [14,15] and estimations based on second-order or higher-order statistics [16,17]; the existing SINR estimations mainly include moment-based estimations [18-20] and subspacebased (SB) eigenvalue decomposition estimations [21,22]. However, the fact that jamming may exist is not taken into account in most existing SNR estimations that only consider the impact that white Gaussian noise (WGN) has. Therefore, it may be difficult to provide accurate channel quality information for system adaption in the presence of jamming. Meanwhile, the existing SINR estimations, which are mainly aimed at the co-channel interference and adjacent channel interference (self-interference) produced by wireless cell systems (like code division multiple address (CDMA) and time division multiple address (TDMA)) and easily processed by equating...

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“…However, the primary reason for using arrays is to produce a directive beam that can be scanned electronically. Although arrays with stationary beams and multiple stationary beams will be discussed in this text, the primary emphasis will be on those arrays that are scanned electronically [1][2][3][4]. The network can be that of any of the wireless communication technologies such as global system for mobile communications, code division multiple access, wireless local loop, WAN, WiFi, and WiMAX [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Phased arrays in communication system based on Taguchi‐neural networks

Smida

Ghayoula

Nemri

et al. 2013

Int J Communication

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SUMMARY Phased antenna array design is one of the most important electromagnetic optimization problems. This research combined the Taguchi method and artificial intelligence methods, used them as the prediction tool in designing parameters for the communication system, and then constructed a set of the optimal parameter analysis flow and steps. In this paper, we present an application of artificial neural networks in the electromagnetic domain. We particularly look at the multilayer perceptron network, which has been the most used of artificial neural networks architectures both in the electromagnetic domain and in the Taguchi optimization technique and describes the Taguchi method to optimize the excitations elements of the linear array to produce a radiation pattern with minimum side lobe level and null placement control. This paper investigates how the implementation of the signal processing in hardware affects the performance of the adaptive array antenna. The investigation is confined to uplink or receive antenna array only. Results of a prototype of antenna array with feeding values designed using the proposed techniques are also presented. Copyright © 2013 John Wiley & Sons, Ltd.

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Channel capacity of multiple‐input multiple‐output ultra‐wideband systems with single co‐channel interference

Cited by 21 publications

References 16 publications

Comparison of different antenna arrays for the channel capacity

Comparison of different antenna arrays for the channel capacity

A blind signal‐to‐jamming‐plus‐noise ratio estimation based on second‐order cyclostationarity under typical tone‐jamming and its CRLB

Phased arrays in communication system based on Taguchi‐neural networks

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