A statistical inter-cell interference model for downlink cellular OFDMA networks under log-normal shadowing and multipath Rayleigh fading

Seol, Changkyu; Cheun, Kyungwhoon

doi:10.1109/tcomm.2009.10.080152

Cited by 71 publications

(54 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The total number of BSs is 19 and the inter-site distance is 100 m. It can be observed that the MoG distribution derived in this paper fits simulation excellently. The generalised Gaussian model proposed in [2,3] and the Gaussian model are also shown in Fig. 7.…”

Section: Results and Analysismentioning

confidence: 99%

See 1 more Smart Citation

Single‐cell and multi‐cell performance analysis of OFDM index modulation

Nekovee

2017

IET Communications

View full text Add to dashboard Cite

This study addresses the achievable rate of single cell and sum rate of multi-cell orthogonal frequency division multiplexing (OFDM) index modulation (IM). The single-cell achievable rate of OFDM-IM with Gaussian input is calculated using a multi-ary symmetric channel. Then, the cumulative distribution function of multi-cell OFDM-IM is investigated by stochastic geometry. Furthermore, it is proved in this study that the probability density function of noise plus inter-cell interference in multicell OFDM-IM with quadrature-amplitude modulation follows a mixture of Gaussians (MoGs) distribution. Next, parameters of the MoG distribution are estimated using a simplified expectation maximisation algorithm. Upper bound of sum rates of multi-cell OFDM-IM is derived. Furthermore, analytic and simulated results are compared and discussed.

show abstract

Section: Results and Analysismentioning

confidence: 99%

“…Gaussian distributions were used to approximate the PDF in [2,3]. In this section, the exact PDF of noise plus ICI will be derived showing that noise plus ICI is MoG distributed.…”

Section: Pdf Of Noise Plus Interferencementioning

confidence: 99%

Single‐cell and multi‐cell performance analysis of OFDM index modulation

Nekovee

2017

IET Communications

View full text Add to dashboard Cite

show abstract

“…We highlight that this assumption becomes more and more valid as the sector load and the number of BSs in the system increase [22]. Basically, as the number of interference sources increases, the central limit theorem can be applied.…”

Section: System Modelingmentioning

confidence: 99%

Joint Resource Block Assignment and Power Allocation Problem for Rate Maximization With QoS Guarantees in Multiservice Wireless

Maurício

Lima

Sousa³

et al. 2016

JCIS

View full text Add to dashboard Cite

Abstract-We formulate the resource and power assignment problem of maximizing the spectral efficiency of a wireless system subject to user satisfaction constraints in the multiservice scenario. We show that although this optimization problem is nonlinear, it can be converted to an integer linear program. In this way, standard techniques can be used to obtain the optimal solution. Motivated by the high computational complexity of the optimal solution, we propose a fast suboptimal algorithm. Simulation results show that our proposal achieves near-optimal performance in low and medium loads with a much lower computational complexity compared with the algorithm used to obtain the optimal solution. Therefore, our proposed algorithm achieves a good tradeoff between performance and computational complexity. We also show that the addition of adaptive power allocation renders significant performance gains in the considered scenario.Index Terms-Multiservice, quality of service (QoS), rate maximization, resource and power assignment.

show abstract

“…In the literature, some works propose methods to mitigate the interference, such as coordination among eNBs and interference alignment [26]- [30]. On the other hand, for the sake of simplicity, some papers treat the inter-cell interference as part of the Additive White Gaussian Noise (AWGN) added to the received signal in the UE, which is valid when the number of UEs and Base Stations (BSs) increases [31]. More detailed/sophisticated interference modeling and mitigation is out of the scope in this paper.…”

Section: Introductionmentioning

confidence: 99%

Resource Management for Rate Maximization with QoE Provisioning in Wireless Networks

Sousa¹,

Monteiro²,

Maciel³

et al. 2016

JCIS

View full text Add to dashboard Cite

Abstract-In this work, we study the problem of allocating resources in a multi-service cellular network aiming at maximizing the total system rate while providing suitable Quality of Experience (QoE) to the network users. In our formulation, we try to satisfy at least a certain number of users per service plan, which is an important constraint from the mobile network operators' perspective. We manage to reformulate this nonlinear optimization problem as an Integer Linear Problem (ILP), that can be solved by standard methods. However, due to the exponentially high complexity to solve large instances of this problem, we propose and evaluate a suboptimal algorithm with a much lower complexity, called Rate Maximization under Experience Constraints (RMEC), whose main idea is to divide the problem into three smaller subproblems with reduced complexity. By means of computational simulations, we show that our proposed algorithm presents a near optimal performance and outperforms the state-of-art solution of the literature.

show abstract

A statistical inter-cell interference model for downlink cellular OFDMA networks under log-normal shadowing and multipath Rayleigh fading

Cited by 71 publications

References 22 publications

Single‐cell and multi‐cell performance analysis of OFDM index modulation

Single‐cell and multi‐cell performance analysis of OFDM index modulation

Joint Resource Block Assignment and Power Allocation Problem for Rate Maximization With QoS Guarantees in Multiservice Wireless

Resource Management for Rate Maximization with QoE Provisioning in Wireless Networks

Contact Info

Product

Resources

About