NICE: A Network Interference Cancellation Engine for Opportunistic Uplink Cooperation in Wireless Networks

Balachandran, K.; Kang, Joseph H.; Karakayali, Kemal; Rege, Kiran M.

doi:10.1109/twc.2010.120610.100169

Cited by 46 publications

(42 citation statements)

References 15 publications

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“…The study in [14] consisted of the cooperation of the base stations equipped with multiple antennas within a cellular system. The proposed interference cancelation was based on multiple antenna signal processing and the exchange of strongly interfering terminal data with the base stations where the received signal decoding remained unsuccessful.…”

Section: Introductionmentioning

confidence: 99%

“…The latter base stations performed successive interference cancellation, which used additional multiple antenna processing. Reference [14] assumed that some base stations in the cell can decode multiple user data using their multiple antennas and then exchange the estimated data with the other base stations. Then, the forwarded data were used for interference cancellation when the signal-to-interference-plus-noise ratio (SINR) at the femtocell due to the MUE interference was negligible.…”

Section: Introductionmentioning

confidence: 99%

“…The concept in [14] reflected more of the version of the traditional successive interference cancellation combined with the network MIMO. The traditional successive interference cancellation involved the extraction of the estimated interfering signal from the combined signals and the estimation of the desired signal from the difference.…”

Section: Introductionmentioning

confidence: 99%

“…The traditional successive interference cancellation involved the extraction of the estimated interfering signal from the combined signals and the estimation of the desired signal from the difference. The system model in [14] lacked reliability because one of the base stations could be unable to estimate the signal of a strongly interfering terminal from the received combined signals. In contrast to [14], the study in this paper uses signaling without resorting to multiple antennas.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Cross-tier interference management with a distributed antenna system for multi-tier cellular networks

Ndong

Fujii

2014

J Wireless Com Network

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In a multi-tier cellular communication system, the interference from one tier to another, denoted as cross-tier interference, is a limiting factor for the system performance. In spectrum-sharing usage, we consider the uplink crosstier interference management of heterogeneous networks using femtocells overlaid onto the macrocells. We propose a variation of the cellular architecture and introduce a novel femtocell clustering based on interference cancellation to enhance the sum rate capacity. Our proposal is to use a distributed antenna system (DAS) as an interface to mitigate the cross-tier interference between the macrocell and femtocell tiers. By placing a DAS remote antenna unit (RAU) near a set of femtocells that experience interference from a macrocell user, the DAS can retrieve the interference symbols and feed them back to the femtocells, where each cell can perform interference cancellation when necessary. In addition, the DAS can forward the recovered data to the macrocell base station (MBS); thus, the macrocell user can reduce its transmit power to reach a RAU located closer than the MBS. By distributing the sensor nodes within the macrocell coverage, the proposed scheme can mitigate the cross-tier interference at different locations for several femtocell clusters. Our simulation results show substantial improvement in the network sum rate capacity.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Cross-tier interference management with a distributed antenna system for multi-tier cellular networks

Ndong

Fujii

2014

J Wireless Com Network

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“…In addition, PHY-layer techniques may be used to cancel the interference and prevent a collision at the receiver [11][12][13]. For example, zero-forcing (ZF) beamforming for interference cancellation has been shown to increase the capacity of ad-hoc networks [14].…”

Section: Introductionmentioning

confidence: 99%

Beamforming techniques for enabling spatial-reuse in MCCA 802.11s networks

Lebrun

Zhao

Pollin

et al. 2011

J Wireless Com Network

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We address the problem of co-channel interference (CCI) in wireless mesh networks based on the IEEE802.11s extension. The carrier sensing mechanism deployed in those networks insufficiently addresses the CCI problem, causing the hidden and exposed node problems; consequently degrading the throughput and latency. In this paper, we show how beamforming techniques can be implemented on top of the IEEE802.11s medium access control protocol and, using the information readily available, cancel the interference to mitigate this inefficiency of carrier sense and improve the spatial-reuse gain. In addition, we propose the signal-to-jamming-noise ratio (SJNR) beamformer and show that it significantly improves the spatial-reuse gain compared to the simple zero-forcing (ZF) beamformer and the basic IEEE802.11s access scheme. We derive the ergodic capacity of the ZF beamformer and the basic IEEE802.11s access scheme and simulate the performance of the various schemes. We show that improvements of up to 85% are achieved as function of the scenario simulated and the beamforming technique used and that the SJNR scheme outperforms the standard ZF beamformer.

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