Interference alignment in clustered ad hoc networks: High reliability regime and per-cluster aloha

Tresch, Roland; Alfano, G.; Guillaud, Maxime

doi:10.1109/icassp.2011.5947102

Cited by 11 publications

(12 citation statements)

References 8 publications

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“…In order to better analyze the performance of an ad hoc network with the IA approach, we derive the upper and lower bounds of the outage probability (OP) and transmission capacity (TC) for PPP ad hoc networks with or without fading. In contrast to [7] and [8], where a Poisson Clustered Process is considered, we use the Poisson distribution to simulate the location of the transmitters, which can better describe the randomness or independence property of the nodes. It is worth mentioning that the IA range is specified in the proposed work, which is more realistic than that used in [9] where the IA range is considered as abstract definition.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of ad hoc networks with interference alignment

Luo

Ratnarajah

et al. 2012

2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)

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The performance of ad hoc networks is fundamentally limited by interference, especially by the interference from nearby transmitting nodes. In this work, we introduce vector space interference alignment (IA) to an ad hoc network scenario to efficiently eliminate interference. However, according to its feasibility conditions, vector space IA is impractical to implement in dense ad hoc networks directly. Therefore, we define an IA range to divide the ad hoc network into smaller local networks. The interference induced by the transmitters located in the prespecified IA range is completely aligned and eliminated via an IA approach. Considering the effect of the interference from the transmitters located outside the IA range, the upper and lower bounds of outage probability and transmission capacity are characterized. Monte Carlo simulation results have validated the performance improvement provided by the proposed IA scheme in ad hoc networks.

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Section: Introductionmentioning

confidence: 99%

Performance analysis of ad hoc networks with interference alignment

Luo

Ratnarajah

et al. 2012

2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)

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“…However, predicting the interference together with fading effects and node distributions is a puzzling problem. [7] The throughput performance of MANET is drastically degraded by a bottleneck of mutual interference. To increase the network throughput, multiple antennas can be implemented at the radio nodes.…”

Section: Interference In Manetmentioning

confidence: 99%

Interference Reduction Technique in Mobile Adhoc Networks using Mathematical Prediction Filters

Suseendran¹,

Chandrasekaran²

2012

IJCA

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Interference is one of the major degrading factors of mobile ad hoc networks (MANET). Since, MANET transmits over the single wireless channel; packets of the same flow interfere with each other greatly. This mutual interference causes the bottleneck over the network. Further, predicting interference accurately around a transmitter or receiver is a complicated task. As a solution to these problems, in this paper, we propose an interference reduction technique for MANET using mathematical prediction filters. The technique used Hidden Markov Model (HMM) for predicting the interference of the nodes. Initial transmission power is set by comparing received signal power with minimum and maximum values. During data transmission, RTS and CTS messages are exchanged using initial transmission power level and they include interference value of the source and destination respectively. The source then uses the interference value of the destination to transmit data packet. On the other hand, the destination uses the interference value of the source for transmitting the acknowledgement (ACK) packet to the source. Thus, this interference calculation at both ends reduces the interference. By simulation, we show that our technique reduces the interference considerably.

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“…Aligning every single additional data stream is an overhead to the beamforming or receiving matrices. Finally, whend a = 0, all nearest cross-tier interferences are modeled as shot noise, which is how IA is implemented in [16], [17]. Clearly, ignoring the nearest crosstier interference is only optimal when l 0N0 is large.…”

Section: Theoremmentioning

confidence: 99%

“…In [19], the full potential of IA was realized by achieving half of the total DoF at each receiver in K-user interference channel. [16] and [17] studied the performance of wireless networks with Poisson clustered process (PCP) based on the probability generating function (PGF) where perfect intra-cluster channel state information (CSI) was available and the intra-cluster interference was completely eliminated by using the IA approach. Moreover, the case of imperfect CSI with bounded errors was considered in [18], and a capacity lower bound of the channel by using IA was derived.…”

Section: Introductionmentioning

confidence: 99%

Interference Alignment in Two-Tier Randomly Distributed Heterogeneous Wireless Networks Using Stochastic Geometry Approach

Luo

Ratnarajah

Xue

et al. 2018

IEEE Systems Journal

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Abstract-With the massive increase in wireless data traffic in recent years, multi-tier wireless networks have been deployed to provide much higher capacities and coverage. However, heterogeneity of wireless networks bring new challenges for interference analysis and coordination due to spatial randomly distributed transmitters. In this paper, we present a distancedependent interference alignment (IA) approach for a generic 2-tier heterogeneous wireless network, where transmitters in the first a nd s econd t iers a re d istributed a s P oisson Point Process (PPP) and Poisson Cluster Process (PCP) respectively. The feasibility condition of the IA approach is used to find upper bound of the number of interference streams that can be aligned. The proposed IA scheme maximizes the second-tier throughput by using the trade-off between signal-to-interference ratio and multiplexing gain. It is shown that acquiring accurate knowledge of the distance between the receiver in the second-tier and the nearest cross-tier transmitter only brings insignificant throughput gain compared to statistical knowledge of distance. Furthermore, the remaining cross-tier and inter-cluster interferences are modeled and analyzed using stochastic geometry technique. Numerical results validate the derived expressions of success probabilities and throughput, and show that the distancedependent IA scheme significantly outperforms the traditional IA scheme in the presence of path-loss effect.

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Interference alignment in clustered ad hoc networks: High reliability regime and per-cluster aloha

Cited by 11 publications

References 8 publications

Performance analysis of ad hoc networks with interference alignment

Performance analysis of ad hoc networks with interference alignment

Interference Reduction Technique in Mobile Adhoc Networks using Mathematical Prediction Filters

Interference Alignment in Two-Tier Randomly Distributed Heterogeneous Wireless Networks Using Stochastic Geometry Approach

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