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22
Offloading in heterogeneous networks: Modeling, analysis and design insights
 IEEE TRANS. WIRELESS COMMUN
, 2013
"... Pushing data traffic from cellular to WiFi is an example of inter radio access technology (RAT) offloading. While this clearly alleviates congestion on the overloaded cellular network, the ultimate potential of such offloading and its effect on overall system performance is not well understood. To ..."
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Cited by 67 (17 self)
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Pushing data traffic from cellular to WiFi is an example of inter radio access technology (RAT) offloading. While this clearly alleviates congestion on the overloaded cellular network, the ultimate potential of such offloading and its effect on overall system performance is not well understood. To address this, we develop a general and tractable model that consists of M different RATs, each deploying up to K different tiers of access points (APs), where each tier differs in transmit power, path loss exponent, deployment density and bandwidth. Each class of APs is modeled as an independent Poisson point process (PPP), with mobile user locations modeled as another independent PPP, all channels further consisting of i.i.d. Rayleigh fading. The distribution of rate over the entire network is then derived for a weighted association strategy, where such weights can be tuned to optimize a particular objective. We show that the optimum fraction of traffic offloaded to maximize SINR coverage is not in general the same as the one that maximizes rate coverage, defined as the fraction of users achieving a given rate.
Fundamentals of Heterogeneous Cellular Networks with Energy Harvesting
 IEEE TRAN. WIRELESS COMMUNICATIONS
, 2014
"... We develop a new tractable model for Ktier heterogeneous cellular networks (HetNets), where each base station (BS) is powered solely by a selfcontained energy harvesting module. The BSs across tiers differ in terms of the energy harvesting rate, energy storage capacity, transmit power and deploym ..."
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Cited by 15 (2 self)
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We develop a new tractable model for Ktier heterogeneous cellular networks (HetNets), where each base station (BS) is powered solely by a selfcontained energy harvesting module. The BSs across tiers differ in terms of the energy harvesting rate, energy storage capacity, transmit power and deployment density. Since a BS may not always have enough energy, it may need to be kept OFF and allowed to recharge while nearby users are served by neighboring BSs that are ON. We show that the fraction of time a kth tier BS can be kept ON, termed availability ρk, is a fundamental metric of interest. Using tools from random walk theory, fixed point analysis and stochastic geometry, we characterize the set of Ktuples (ρ1, ρ2,... ρK), termed the availability region, that is achievable by general uncoordinated operational strategies, where the decision to toggle the current ON/OFF state of a BS is taken independently of the other BSs. If the availability vector corresponding to the optimal system performance, e.g., in terms of rate, lies in this availability region, there is no performance loss due to the presence of unreliable energy sources. As a part of our analysis, we model the temporal dynamics of the energy level at each BS as a birthdeath process, derive the energy utilization rate, and use hitting/stopping time analysis to prove that there exists a fundamental limit on ρk that cannot be surpassed by any uncoordinated strategy.
Modeling, analysis, and design for carrier aggregation in heterogeneous cellular networks
 IEEE Tran. Commun
, 2013
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Downlink MIMO HetNets: Modeling, Ordering Results and Performance Analysis
 IEEE TRANS. ON WIRELESS COMMUN
, 2013
"... We develop a general downlink model for multiantenna heterogeneous cellular networks (HetNets), where base stations (BSs) across tiers may differ in terms of transmit power, target signaltointerferenceratio (SIR), deployment density, number of transmit antennas and the type of multiantenna tr ..."
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Cited by 14 (6 self)
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We develop a general downlink model for multiantenna heterogeneous cellular networks (HetNets), where base stations (BSs) across tiers may differ in terms of transmit power, target signaltointerferenceratio (SIR), deployment density, number of transmit antennas and the type of multiantenna transmission. In particular, we consider and compare space division multiple access (SDMA), single user beamforming (SUBF), and baseline singleinput singleoutput (SISO) transmission. For this general model, the main contributions are: (i) ordering results for both coverage probability and per user rate in closed form for any BS distribution for the three considered techniques, using novel tools from stochastic orders, (ii) upper bounds on the coverage probability assuming a Poisson BS distribution, and (iii) a comparison of the area spectral efficiency (ASE). The analysis concretely demonstrates, for example, that for a given total number of transmit antennas in the network, it is preferable to spread them across many singleantenna BSs vs. fewer multiantenna BSs. Another observation is that SUBF provides higher coverage and per user data rate than SDMA, but SDMA is in some cases better in terms of ASE.
Modeling nonuniform UE distributions in downlink cellular networks
 IEEE Wireless Commun. Letters
, 2013
"... Abstract—A recent way to model and analyze downlink cellular networks is by using random spatial models. Assuming user equipment (UE) distribution to be uniform, the analysis is performed at a typical UE located at the origin. At least one shortcoming of this approach is its inability to model non ..."
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Cited by 13 (4 self)
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Abstract—A recent way to model and analyze downlink cellular networks is by using random spatial models. Assuming user equipment (UE) distribution to be uniform, the analysis is performed at a typical UE located at the origin. At least one shortcoming of this approach is its inability to model nonuniform UE distributions, especially when there is dependence in the UE and the base station (BS) locations. To facilitate analysis in such cases, we propose a new tractable method of sampling UEs by conditionally thinning the BS point process and show that the resulting framework can be used as a tractable generative model to study current capacitycentric deployments, where the UEs are more likely to lie closer to the BSs. Index Terms—Cellular networks, nonuniform UE distribution, stochastic geometry, coverage probability. I.
Average rate of downlink heterogeneous cellular networks over generalized fading channels – A stochastic geometry approach
 IEEE Trans. Commun
, 2013
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1 Hybrid Full/HalfDuplex System Analysis in Heterogeneous Wireless Networks
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Unified and Distributed QoSDriven Cell Association Algorithms in Heterogeneous Networks
, 2014
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1Fundamentals of Base Station Availability in Cellular Networks with Energy Harvesting
"... Abstract—We develop a new tractable model forKtier cellular networks, where each base station (BS) is solely powered by a selfcontained energy harvesting module instead of a conventional powerline source. The BSs across tiers differ in terms of the energy harvesting rate, energy storage capacity, ..."
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Cited by 1 (1 self)
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Abstract—We develop a new tractable model forKtier cellular networks, where each base station (BS) is solely powered by a selfcontained energy harvesting module instead of a conventional powerline source. The BSs across tiers differ in terms of the energy harvesting rate, energy storage capacity, transmit power and deployment density. Since a BS may not always have enough energy, it may need to be kept OFF and allowed to recharge while its load is served by the neighboring BSs that are ON. Using tools from random walk theory and stochastic geometry, we characterize the fraction of time each type of BS can be kept ON, termed availability, for general uncoordinated strategies, where each BS toggles its ON/OFF state independently of the others. As a part of our analysis, we model the temporal dynamics of the energy level at each BS as a birthdeath process, derive energy utilization rate for each BS class, and use hitting/stopping time analysis to study availabilities. We prove that there is a fundamental limit on the availabilities, which cannot be surpassed by any uncoordinated strategy. As a part of the proof, we construct the strategy that achieves this limit. I.
Traffic Driven Resource Allocation in Heterogenous Wireless Networks
"... Abstract—Most work on wireless network resource allocation use physical layer performance such as sum rate and outage probability as the figure of merit. These metrics may not reflect the true user QoS in future heterogenous networks (HetNets) with many small cells, due to large traffic variations i ..."
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Abstract—Most work on wireless network resource allocation use physical layer performance such as sum rate and outage probability as the figure of merit. These metrics may not reflect the true user QoS in future heterogenous networks (HetNets) with many small cells, due to large traffic variations in overlapping cells with complicated interference conditions. This paper studies the spectrum allocation problem in HetNets using the average packet sojourn time as the performance metric. To be specific, in a HetNet with K base terminal stations (BTS’s), we determine the optimal partition of the spectrum into 2K possible spectrum sharing combinations. We use an interactive queueing model to characterize the flow level performance, where the service rates are decided by the spectrum partition. The spectrum allocation problem is formulated using a conservative approximation, which makes the optimization problem convex. We prove that in the optimal solution the spectrum is divided into at most K pieces. A numerical algorithm is provided to solve the spectrum allocation problem on a slow timescale with aggregate traffic and service information. Simulation results show that the proposed solution achieves significant gains compared to both orthogonal and full spectrum reuse allocations with moderate to heavy traffic. I.