Downlink interference estimation without feedback for heterogeneous network interference avoidance

Wang, Siyi; Guo, Weisi; McDonnell, Mark D.

doi:10.1109/ict.2014.6845085

Cited by 10 publications

(19 citation statements)

References 15 publications

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“…In [13], an interference estimation technique that does not require information sharing between BSs or UEs was devised based on each BS sensing the spectrum and estimating the number of co-channel transmissions in a defined observation zone. By estimating the number of cochannel transmitters and knowing the cell density in the region, the average channel quality at any random point in a coverage area can be inferred.…”

Section: A Inference Frameworkmentioning

confidence: 99%

Coexistence of Wi-Fi and heterogeneous small cell networks sharing unlicensed spectrum

et al. 2015

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As two major players in terrestrial wireless communications, Wi-Fi systems and cellular networks have different origins and have largely evolved separately. Motivated by the exponentially increasing wireless data demand, cellular networks are evolving towards a heterogeneous and small cell network architecture, wherein small cells are expected to provide very high capacity. However, due to the limited licensed spectrum for cellular networks, any effort to achieve capacity growth through network densification will face the challenge of severe inter-cell interference. In view of this, recent standardization developments have started to consider the opportunities for cellular networks to use the unlicensed spectrum bands, including the 2.4 GHz and 5 GHz bands that are currently used by Wi-Fi, Zigbee and some other communication systems. In this article, we look into the coexistence of Wi-Fi and 4G cellular networks sharing the unlicensed spectrum. We introduce a network architecture where small cells use the same unlicensed spectrum that Wi-Fi systems operate in without affecting the performance of Wi-Fi systems. We present an almost blank subframe (ABS) scheme without priority to mitigate the co-channel interference from small cells to Wi-Fi systems, and propose an interference avoidance scheme based on small cells estimating the density of nearby Wi-Fi access points to facilitate their coexistence while sharing the same unlicensed spectrum. Simulation results show that the proposed network architecture and interference avoidance schemes can significantly increase the capacity of 4G heterogeneous cellular networks while maintaining the service quality of Wi-Fi systems.

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Section: A Inference Frameworkmentioning

confidence: 99%

Coexistence of Wi-Fi and heterogeneous small cell networks sharing unlicensed spectrum

et al. 2015

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“…The parameters for the above equations are as follows: W is the AWGN power, H is the fading gain, P is the transmission power, Λ is the density of the transmitters, λ is the frequency dependent pathloss constant, r j,j is the distance between the transmitter and receiver D2D UEs, Ψ is the radius of the network coverage area for which an accurate BS density Λ can be determined [20], and α is the pathloss distance exponent. Typically, the aggregate interference power is significantly higher than the additive noise power W , and one can be assumed that the noise power is negligible.…”

Section: D2d Ues Distribution and Receiver Sinrmentioning

confidence: 99%

Interference‐aware multi‐hop path selection for device‐to‐device communications in a cellular interference environment

et al. 2017

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Minming. (2017) Interference-aware multi-hop path selection for device-to-device communications in a cellular interference environment. IET Communications. Permanent WRAP URL:http://wrap.warwick.ac.uk/87352 Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. Publisher's statement:"This paper is a postprint of a paper submitted to and accepted for publication in IET Communications and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library" A note on versions: The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription. Abstract: Device-to-Device (D2D) communications is widely seen as an efficient network capacity scaling technology. The co-existence of D2D with conventional cellular (CC) transmissions causes unwanted interference. Existing techniques have focused on improving the throughput of D2D communications by optimising the radio resource management and power allocation. However, very little is understood about the impact of the route selection of the users and how optimal routing can reduce interference and improve the overall network capacity. In fact, traditional wisdom indicates that minimising the number of hops or the total path distance is preferable. Yet, when interference is considered, we show that this is not the case. In this paper, we show that by understanding the location of the user, an interference-aware routing algorithm can be devised. We propose an adaptive Interference-Aware-Routing (IAR) algorithm, that on average achieves a 30% increase in hop distance, but can improve the overall network capacity by 50% whilst only incurring a minor 2% degradation to the CC capacity. The analysis framework and the results open up new avenues of research in location-dependent optimization in wireless systems, which is particularly important for increasingly dense and semantic-aware deployments.

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“…The distance between the UE and the first interfering eNB is then estimated with the mean, median and mode estimators (Eq (11) (12) and (13)), based on the RSRP measured at the UE level. Since the RSRP is measured over one RE and not over all the considered bandwidth, then the performance evaluation is given with distance estimated according to: (i) one RSRP measurement (i.e., the worst case) and (ii) an average RSRP value, obtained from the RSRPs measured on the Positioning Reference Signals (PRS) in the considered bandwidth as defined in the standard [21].…”

Section: Evaluation Of the Location-dependent Ici Estimation Modementioning

confidence: 99%

“…end for 2-u k ranks the RSRPs: V = sort(RSRP (k,i) ), 3-u k identifies the donor eNBs V (1), 4-u k identifies the most interfering eNB V (2) and estimate its ranger (i,k) using Eq. (11) (12) and (13) …”

Section: Algorithm 1 Location Dependent Ici Estimation Algorithmmentioning

confidence: 99%

“…Location-dependent ICI estimation models derive an analytical expression of the ICI level as a function of UEs locations. In [11] and [12], location-dependent ICI estimation model are proposed, respectively for random wireless network and ktier Heterogeneous Network (HetNet), where the shadowing impact are neglected and only the fast fading is considered. In our previous work [13], we proposed a new locationdependent ICI estimation model in a random HetNet, that evaluate the ICI level as a function of the UE location (more specially the distance between the UE and the most interfering eNB), considering both fast fading and shadowing effects.…”

Section: Introductionmentioning

confidence: 99%

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Accuracy of Location-Dependent Inter-Cell Interference Stochastic Model with Ranging Errors

Kaddour

Denis

Kténas

2015

2015 IEEE 81st Vehicular Technology Conference (VTC Spring)

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This paper investigate the accuracy of the locationdependent Inter-Cell Interference (ICI) level predicted taking into account shadowing effect in downlink heterogeneous cellular networks. The model accuracy is studied with respect to the distance range estimation reliability, where the distance between the User Equipement (UE) and its most interfering eNB is estimated according to the Reference Signal Strength (RSS) ranging method. The log-normal shadowing path loss model is considered, where three distance estimators are used: mean, median and mode. The reliability of these ones is discussed in macro and small cell scenarios. Then, the impact of distance error estimation in both scenarios is evaluated.

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Downlink interference estimation without feedback for heterogeneous network interference avoidance

Cited by 10 publications

References 15 publications

Coexistence of Wi-Fi and heterogeneous small cell networks sharing unlicensed spectrum

Coexistence of Wi-Fi and heterogeneous small cell networks sharing unlicensed spectrum

Interference‐aware multi‐hop path selection for device‐to‐device communications in a cellular interference environment

Accuracy of Location-Dependent Inter-Cell Interference Stochastic Model with Ranging Errors

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