Distributed algorithm for downlink resource allocation in multicarrier small cell networks

Ahmed, Furqan; Dowhuszko, Alexis A.; Tirkkonen, Olav

doi:10.1109/icc.2012.6364716

Cited by 23 publications

(14 citation statements)

References 17 publications

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“…The current paper generalizes the analysis presented in [26], where a distributed algorithm is discussed for transmit power and scheduling weight allocation in a multi-carrier SCN. The generalization is in two directions.…”

Section: B Contributionsmentioning

confidence: 77%

Self-Organizing Algorithms for Interference Coordination in Small Cell Networks

Ahmed

Dowhuszko

Tirkkonen

2017

IEEE Trans. Veh. Technol.

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This paper discusses novel joint (intra-cell and inter-cell) resource allocation algorithms for self-organized interference coordination in multi-carrier multiple-input multipleoutput (MIMO) small cell networks (SCNs). The proposed algorithms enable interference coordination autonomously, over multiple degrees of freedom, such as base station transmit powers, transmit precoders, and user scheduling weights. A generic α-fair utility maximization framework is considered to analyze performance-fairness trade-off, and to quantify the gains achievable in interference-limited networks. The proposed scheme involves limited inter-base station signaling in the form of two step (power and precoder) pricing. Based on this decentralized coordination, autonomous power and precoder update decision rules are considered, leading to algorithms with different characteristics in terms of user data rates, signaling load, and convergence speed. Simulation results in a practical setting show that the proposed pricing-based self-organization can achieve up to 100% improvement in cell-edge data rates, when compared to baseline optimization strategies. Furthermore, the convergence of the proposed algorithms is also proved theoretically.Index Terms-Self-organizing networks, autonomous algorithms, interference coordination, resource allocation, multipleinput multiple-output, co-channel interference, small cell networks, network utility maximization.

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Section: B Contributionsmentioning

confidence: 77%

Self-Organizing Algorithms for Interference Coordination in Small Cell Networks

Ahmed

Dowhuszko

Tirkkonen

2017

IEEE Trans. Veh. Technol.

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“…Femtocells are essentially user-deployed, indoor, small cells. Regardless of the details of the system under consideration, they can be categorized into autonomous power control [8]- [12] and adaptive spectrum allocation [13]- [18]. The main feature of the first group is to adjust the AP coverage by setting the transmit power high enough to service its users but low enough so as not to interfere with the other APs on the same frequency of operation.…”

Section: A Related Workmentioning

confidence: 99%

Partially-Distributed Resource Allocation in Small-Cell Networks

Sadr

Adve

2014

IEEE Trans. Wireless Commun.

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We propose a four-stage hierarchical resource allocation scheme for the downlink of a large-scale small-cell network in the context of orthogonal frequency-division multiple access (OFDMA). Since interference limits the capabilities of such networks, resource allocation and interference management are crucial. However, obtaining the globally optimum resource allocation is exponentially complex and mathematically intractable. Here, we develop a partially decentralized algorithm to obtain an effective solution. The three major advantages of our work are: 1) as opposed to a fixed resource allocation, we consider load demand at each access point (AP) when allocating spectrum; 2) to prevent overloaded APs, our scheme is dynamic in the sense that as the users move from one AP to the other, so do the allocated resources, if necessary, and such considerations generally result in huge computational complexity, which brings us to the third advantage: 3) we tackle complexity by introducing a hierarchical scheme comprising four phases: user association, load estimation, interference management via graph coloring, and scheduling. We provide mathematical analysis for the first three steps modeling the user and AP locations as Poisson point processes. Finally, we provide results of numerical simulations to illustrate the efficacy of our scheme.Comment: Accepted on May 15, 2014 for publication in the IEEE Transactions on Wireless Communication

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“…In what follows, we discuss decomposition methods that lead to pricing algorithms for finding a solution of (8) in a distributed way. Note that in frequency selective channels, this model would naturally generalize to the multichannel version of the power allocation problem, which is non-convex [12].…”

Section: Introductionmentioning

confidence: 98%

Distributed Power Allocation in Cognitive Radio Networks under Network Power Constraint

Ahmed¹,

Tirkkonen²,

Dowhuszko³

et al. 2014

Proceedings of the 9th International Conference on Cognitive Radio Oriented Wireless Networks

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We consider utility maximization in a multi-cell network under a total transmit power constraint, e.g. given by a cognitive radio geo-location database. The network utility in the downlink is maximized by allocating transmit powers in the network, while meeting the network-wide transmit power constraint. Distributed algorithms for allocating downlink transmit power are discussed, which involve exchange of prices that reflect interference between cells. Using primal decomposition, we present an online algorithm which guarantees that the network power constraint is met at all times. To this end, each cell adjusts its power level while taking into account the interference prices received from neighboring cells. Depending on the pricing information, a transmitter may reduce its power so that it can be used by some other transmitter. Distributed optimization enabled by the exchange of interference prices among cells results in an efficient distribution of total power among the transmitters. Simulation results illustrate that exchange of prices can yield a significant gain over non-cooperative and partially cooperative power allocation approaches in indoor small multi-cell networks.

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Distributed algorithm for downlink resource allocation in multicarrier small cell networks

Cited by 23 publications

References 17 publications

Self-Organizing Algorithms for Interference Coordination in Small Cell Networks

Self-Organizing Algorithms for Interference Coordination in Small Cell Networks

Partially-Distributed Resource Allocation in Small-Cell Networks

Distributed Power Allocation in Cognitive Radio Networks under Network Power Constraint

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