MIMO interference alignment in random access networks

Nosrat-Makouei, Behrang; Andrews, Jeffrey G.; Heath, Robert W.; Ganti, Radha Krishna

doi:10.1109/acssc.2011.6190081

Cited by 11 publications

(7 citation statements)

References 33 publications

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“…The BSs may differ in terms of transmit powers, node densities, and link reliabilities. Such an approach has been considered in [18] for ad-hoc networks and in [19] for random access networks with interference alignment but the key metrics of outage, coverage, and rate have not been determined for HetNets. The main advantage of this approach is that our results combined with that of [14], [15] provide complete theoretical tools to model interference over an urban and rural area whether it is clustered or not.…”

Section: B Motivation and Contributionsmentioning

confidence: 99%

“…Zero intra-cluster interference is widely adopted in the literature [21]- [25]. There are several ways to remove the intra-cluster interference; For example, the central cluster head can orthogonalize the channel access, or intra-cluster interference alignment in [19] can be utilized for the random access channel, or the BSs within the cluster can share the channel state information and use zeroforcing precoding to completely eliminate the intra-cluster interference. In this paper, we consider orthogonal multiple access to simplify the analytical derivation.…”

Section: A System Modelmentioning

confidence: 99%

“…If x and y are uniformly distributed around a circle with radius R, then we can express x − y in polar representation where θ ∼ U (0, 2π) and the PDF of r is given by h(r) in [19].…”

Section: Appendix Imentioning

confidence: 99%

See 2 more Smart Citations

Modeling Heterogeneous Cellular Networks Interference Using Poisson Cluster Processes

Chun

Hasna

Ghrayeb

2015

IEEE J. Select. Areas Commun.

135

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Future mobile networks are converging towards heterogeneous multi-tier networks, where macro-, pico-and femto-cells are randomly deployed based on user demand. A popular approach for analyzing heterogeneous networks (HetNets) is to use stochastic geometry and treat the location of the BSs as points distributed according to a homogeneous Poisson point process (PPP). However, the PPP model does not provide an accurate model for the interference when the nodes are clustered around highly populated areas. This motivates us to find better ways to characterize the aggregate interference when the transmitting nodes are clustered following a Poisson Cluster Process (PCP), while taking into consideration that BSs belonging to different tiers may differ in terms of transmit power, node densities, and link reliabilities. To this end, we consider K-tier HetNets and investigate the outage probability, the coverage probability, and the average achievable rate for such networks. We compare the performance of HetNets when the nodes are clustered and otherwise. By comparing these two types of networks, we conclude that the fundamental difference between PPP and PCP is that for PPP, the number of simultaneously covered mobiles and the network capacity increase linearly with K. However, for PCP, the improvements in coverage and capacity diminish as K grows larger, where the curves saturate at some point. Based on these observations, we determine the scenarios that jointly maximize the average achievable rate and minimize the outage probability.

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Section: B Motivation and Contributionsmentioning

confidence: 99%

Section: A System Modelmentioning

confidence: 99%

See 1 more Smart Citation

Modeling Heterogeneous Cellular Networks Interference Using Poisson Cluster Processes

Chun

Hasna

Ghrayeb

2015

IEEE J. Select. Areas Commun.

135

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

“…PCPs have attracted lots of attention in cellular networks and wireless sensor networks [27]- [33], recently. In [27], an interference alignment approach has been used for a cluster topology to address intra-cluster interference for multipleinput multiple-output (MIMO) systems, where a spatial PCP process is used to model the nodes in a random access network. For heterogeneous cellular networks, PCP has been adopted in [28], [29] to model nodes clustering at hot spots while taking into consideration the fact that base stations belonging to different tiers may differ in terms of transmit power, node density, and link reliability.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Clustered LoRa Networks

Qin

Liu

et al. 2019

IEEE Trans. Veh. Technol.

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In this paper, we investigate the uplink transmission performance of low-power wide-area (LPWA) networks with regards to coexisting radio modules. We adopt long range (LoRa) radio technique as an example of the network of focus even though our analysis can be easily extended to other situations. We exploit a new topology to model the network, where the node locations of LoRa follow a Poisson cluster process (PCP) while other coexisting radio modules follow a Poisson point process (PPP). Unlike most of the performance analysis based on stochastic geometry, we take noise into consideration. More specifically, two models, with a fixed and a random number of active LoRa nodes in each cluster, respectively, are considered. To obtain insights, both the exact and simple approximated expressions for coverage probability are derived. Based on them, area spectral efficiency and energy efficiency are obtained. From our analysis, we show how the performance of LPWA networks can be enhanced through adjusting the density of LoRa nodes around each LoRa receiver. Moreover, the simulation results unveil that the optimal number of active LoRa nodes in each cluster exists to maximize the area spectral efficiency.

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On the performance of asynchronous ad‐hoc networks using interference alignment with renewal process

Luo

Xue

et al. 2013

IET Communications

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The performance of ad-hoc networks is greatly affected by interference, particularly interference from nearby nodes. Based on stochastic geometry, this work studies a form of multiple-input-multiple-output (interference alignment (IA) that eliminates interference from transmitters within a range and treats the remaining interference as a shot noise process. Adapting to the bursty nature of ad-hoc network traffic, the authors introduce a novel distributed ad-hoc network with renewal process, whereby cooperation between interferer and receiver is implemented in one-way process, which results from the difficulties for the node to change the beamforming or receiving matrix whereas communicating with a proposed transmitter. In addition, this scheme takes advantage of IA, leaving the desired signal with higher degree of freedom (DoF) compared with the partially zero-forcing method. Outage probability and transmission capacity are derived with and without Rayleigh fading. Simulation results show the effect of IA in ad-hoc network, including the incremental in the DoF of the desired signal as time goes by. Monte Carlo simulations are implemented and show that IA outperforms successive interference cancellation by at least 10 dB in terms of the signal-to-interference ratio with large path-loss exponent.

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MIMO interference alignment in random access networks

Cited by 11 publications

References 33 publications

Modeling Heterogeneous Cellular Networks Interference Using Poisson Cluster Processes

Modeling Heterogeneous Cellular Networks Interference Using Poisson Cluster Processes

Performance Analysis of Clustered LoRa Networks

On the performance of asynchronous ad‐hoc networks using interference alignment with renewal process

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