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Structured Spectrum Allocation and User Association in Heterogeneous Cellular Networks
, 2014
"... We study joint spectrum allocation and user association in heterogeneous cellular networks with multiple tiers of base stations. A stochastic geometric approach is applied as the basis to derive the average downlink user data rate in a closed-form expression. Then, the expression is employed as the ..."
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Cited by 11 (8 self)
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We study joint spectrum allocation and user association in heterogeneous cellular networks with multiple tiers of base stations. A stochastic geometric approach is applied as the basis to derive the average downlink user data rate in a closed-form expression. Then, the expression is employed as the objective function in jointly optimizing spectrum allocation and user association, which is of non-convex programming in nature. A computationally efficient Structured Spectrum Allocation and User Association (SSAUA) approach is proposed, solving the optimization problem optimally when the density of users is low, and near-optimally with a guaranteed performance bound when the density of users is high. A Surcharge Pricing Scheme (SPS) is also presented, such that the designed association bias values can be achieved in Nash equilibrium. Simulations and numerical studies are conducted to validate the accuracy and efficiency of the proposed SSAUA approach and SPS.
Joint base-station association, channel assignment, beamforming and power control in heterogeneous networks
- Proc. IEEE 75th Veh. Technol. Conf. (VTC
, 2012
"... Abstract—Heterogeneous cellular networks (HetNets), where low-power base-stations are overlaid with conventional macro base-stations, is a promising technique to improve coverage and capacity of the macro-only networks. To realize the potential benefits of HetNets, it is crucial to jointly optimize ..."
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Cited by 9 (3 self)
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Abstract—Heterogeneous cellular networks (HetNets), where low-power base-stations are overlaid with conventional macro base-stations, is a promising technique to improve coverage and capacity of the macro-only networks. To realize the potential benefits of HetNets, it is crucial to jointly optimize the user association, channel assignment, beamforming and power control to ensure that the inter- and intra-cell interference will not overwhelm the cell-splitting gains. This paper presents an iterative algorithm to solve the joint optimization problem with an objective of maximizing the network sum rate and simultaneously guaranteeing the individual user quality-of-service. The proposed algorithm is built on the so-called convex-concave procedure, and the feasibility issue is handled by l1-norm heuristic. Numerical results demonstrate the large gains over currently used methods for cellular networks.
Nonconcave Utility Maximization in Locally Coupled Systems, With Applications to . . .
- IEEE/ACM TRANSACTIONS ON NETWORKING
, 2012
"... Motivated by challenging resource allocation is-sues arising in large-scale wireless and wireline communication networks, we study distributed network utility maximization problems with a mixture of concave (e.g., best-effort throughputs) and nonconcave (e.g., voice/video streaming rates) utilities. ..."
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Cited by 5 (0 self)
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Motivated by challenging resource allocation is-sues arising in large-scale wireless and wireline communication networks, we study distributed network utility maximization problems with a mixture of concave (e.g., best-effort throughputs) and nonconcave (e.g., voice/video streaming rates) utilities. In the first part of the paper, we develop our methodological framework in the context of a locally coupled networked system, where nodes represent agents that control a discrete local state. Each node has a possibly nonconcave local objective function, which depends on the local state of the node and the local states of its neighbors. The goal is to maximize the sum of the local objective functions of all nodes. We devise an iterative randomized algorithm, whose convergence and optimality properties follow from the classical framework of Markov Random Fields and Gibbs Measures via a judiciously selected neighborhood structure. The proposed algorithm is distributed, asynchronous, requires limited computa-tional effort per node/iteration, and yields provable convergence in the limit. In order to demonstrate the scope of the proposed methodological framework, in the second part of the paper we show how the method can be applied to two different problems for which no distributed algorithm with provable convergence and optimality properties is available. Specifically, we describe how the proposed methodology provides a distributed mechanism for solving nonconcave utility maximization problems: 1) arising in OFDMA cellular networks, through power allocation and user assignment; 2) arising in multihop wireline networks, through explicit rate allocation. Several numerical experiments are presented to illustrate the convergence speed and performance of the proposed method.
On Small Cell Network Deployment: A Comparative Study of Random and Grid Topologies
, 2012
"... Abstract—Small cell network is designed to provide mobile services to hot spots by deploying a large number of small access points (APs). As traditional network deployment requires costly AP location acquisition, cost-effective network deployment is necessary for small cell networks. We investigate ..."
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Cited by 3 (0 self)
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Abstract—Small cell network is designed to provide mobile services to hot spots by deploying a large number of small access points (APs). As traditional network deployment requires costly AP location acquisition, cost-effective network deployment is necessary for small cell networks. We investigate this question by studying the network performance in terms of spatial outage and throughput of a completely random topology in comparison to that of a perfectly regular topology. Using a stochastic geometry model of user SINR in a random topology, our results show that the performance gap in terms of user SINR guarantee becomes narrow when the network density increases during the network densification. By a massive deployment, the loss is about 1 dB. Besides, it is at about 18 % loss in user average throughput. These comparative results would provide helpful information to choose an appropriate deployment. In particular, as far as this relatively small performance loss can be compensated by other network control algorithms, the massive random deployment of a small cell network becomes attractive considering the cost reduction by the given deployment freedom. Index Terms—Small cell networks, massive deployment, lognormal interferers, outage probability, user signal quality. I.
2012, <10.1186/1687-1499-2012-273>. <hal-00745107>
, 2012
"... HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
Author manuscript, published in "EURASIP Journal on Wireless Communications and Networking (2012)" DOI: 10.1186/1687-1499-2012-273 Gibbsian Method for the Self-Optimization of Cellular Networks
, 2012
"... In this work, we propose and analyze a class of distributed algorithms performing the joint optimization of radio resources in heterogeneous cellular networks made of a juxtaposition of macro and small cells. Within this context, it is essential to use algorithms able to simultaneously solve the pro ..."
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In this work, we propose and analyze a class of distributed algorithms performing the joint optimization of radio resources in heterogeneous cellular networks made of a juxtaposition of macro and small cells. Within this context, it is essential to use algorithms able to simultaneously solve the problems of channel selection, user association and power control. In such networks, the unpredictability of the cell and user patterns also requires distributed optimization schemes. The proposed method is inspired from statistical physics and based on the Gibbs sampler. It does not require the concavity/convexity, monotonicity or duality properties common to classical optimization problems. Besides, it supports discrete optimization which is especially useful to practical systems. We show that it can be implemented in a fully distributed way and nevertheless achieves system-wide optimality. We use simulation to compare this solution to today’s default operational methods in terms of both throughput and energy consumption. Finally, we address concrete issues for the implementation of this solution and analyze the overhead traffic required within the framework of 3GPP and femtocell standards. 1 1
MATCHING THEORY FOR PRIORITY-BASED CELL ASSOCIATION IN THE DOWNLINK OF WIRELESS SMALL CELL NETWORKS
"... ar ..."
1Capacity and Stable Scheduling in Heterogeneous Wireless Networks
, 2014
"... Heterogeneous wireless networks (HetNets) provide a means to increase network capacity by introducing small cells and adopting a layered architecture. HetNets allocate resources flexibly through time sharing and cell range expansion/contraction allowing a wide range of possible schedulers. In this p ..."
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Heterogeneous wireless networks (HetNets) provide a means to increase network capacity by introducing small cells and adopting a layered architecture. HetNets allocate resources flexibly through time sharing and cell range expansion/contraction allowing a wide range of possible schedulers. In this paper we define the capacity of a HetNet down link in terms of the maximum number of downloads per second which can be achieved for a given offered traffic density. Given this definition we show that the capacity is determined via the solution to a continuous linear program (LP). If the solution is smaller than 1 then there is a scheduler such that the number of mobiles in the network has ergodic properties with finite mean waiting time. If the solution is greater than 1 then no such scheduler exists. The above results continue to hold if a more general class of schedulers is considered.
1User Association for Load Balancing in Heterogeneous Cellular Networks
"... For small cell technology to significantly increase the capacity of tower-based cellular networks, mobile users will need to be actively pushed onto the more lightly loaded tiers (corresponding to, e.g., pico and femtocells), even if they offer a lower instantaneous SINR than the macrocell base stat ..."
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For small cell technology to significantly increase the capacity of tower-based cellular networks, mobile users will need to be actively pushed onto the more lightly loaded tiers (corresponding to, e.g., pico and femtocells), even if they offer a lower instantaneous SINR than the macrocell base station (BS). Optimizing a function of the long-term rates for each user requires (in general) a massive utility maximization problem over all the SINRs and BS loads. On the other hand, an actual implementation will likely resort to a simple biasing approach where a BS in tier j is treated as having its SINR multiplied by a factor Aj ≥ 1, which makes it appear more attractive than the heavily-loaded macrocell. This paper bridges the gap between these approaches through several physical relaxations of the network-wide association problem, whose solution is NP hard. We provide a low-complexity distributed algorithm that converges to a near-optimal solution with a theoretical performance guarantee, and we observe that simple per-tier biasing loses surprisingly little, if the bias values Aj are chosen carefully. Numerical results show a large (3.5x) throughput gain for cell-edge users and a 2x rate gain for median users relative to a maximizing received power association. I.
Utility Optimization in Heterogeneous Networks via CSMA-Based Algorithms
"... Abstract—We study algorithms for carrier and rate allocation in cellular systems with distributed components such as a het-erogeneous LTE system with macrocells and femtocells. Existing work on LTE systems often involves centralized techniques or requires significant signaling, and is therefore not ..."
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Abstract—We study algorithms for carrier and rate allocation in cellular systems with distributed components such as a het-erogeneous LTE system with macrocells and femtocells. Existing work on LTE systems often involves centralized techniques or requires significant signaling, and is therefore not always applicable in the presence of femtocells. More distributed CSMA-based algorithms (carrier-sense multiple access) were developed in the context of 802.11 systems and have been proven to be utility optimal. However, the proof typically assumes a single transmission rate on each carrier. Further, it relies on the CSMA collision detection mechanisms to know whether a transmission is feasible. In this paper we present a framework for LTE scheduling that is based on CSMA techniques. In particular we first prove that CSMA-based algorithms can be generalized to handle multiple transmission rates in a multi-carrier setting while maintaining utility optimality. We then show how such an algorithm can be implemented in a heterogeneous LTE system where the existing Channel Quality Indication (CQI) mechanism is used to decide transmission feasibility. I.
