Sum-Rate Maximization for Multicell OFDMA Systems

Kim, Sung-Yeon; Kwon, Jeong-Ahn; Lee, Jang-Won

doi:10.1109/tvt.2014.2363476

Cited by 23 publications

(26 citation statements)

References 33 publications

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“…The simulation results in Figs. 7a and 7b confirm the analytical analysis of computational complexity according to (13). Similarly, Figs.…”

Section: A Computational Complexitysupporting

confidence: 78%

“…Such schemes are, in general, sub-optimal in practice especially in the case of non-uniform user distribution or the case of a large number of cell-edge users. There exists a large body of research conducted in resource allocation for multicell traditional wireless networks, e.g., in [13], [14], [15], [16], [17], [18], [19], [20]. In this type of works, the BS assignment algorithm is separated from the sub-carrier allocation, while joint sub-carrier and power allocation is applied for multicell scenario.…”

Section: B Related Workmentioning

confidence: 99%

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User Association in Cloud RANs with Massive MIMO

Parsaeefard

Jumba

Shoaei

et al. 2021

IEEE Trans. Cloud Comput.

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This paper studies a resource allocation problem where a set of users within a specific region is served by cloud radio access network (C-RAN) structure consisting of a set of base-band units (BBUs) connected to a set of radio remote heads (RRHs) equipped with a large number of antennas via limited capacity front-haul links. User association to each RRH, BBU and front-haul link is essential to achieve high rates for cell-edge users under network limitations. We introduce two types of optimization variables to formulate this resource allocation problem: (i) C-RAN user association factor (UAF) including RRH, BBU and front-haul allocation for each user and (ii) power allocation vector. The formulated optimization problem is non-convex with high computational complexity. An efficient two-level iterative approach is proposed. The higher level consists of two steps where, in each step, one of these two optimization variables is fixed to derive the other. At the lower level, by applying different transformations and convexification techniques, the optimization problem in each step is broken down into a sequence of geometric programming (GP) problems to be solved by the successive convex approximation (SCA). Simulation results reveal the effectiveness of the proposed approach to increase the total throughput of network, specifically for cell-edge users. It outperforms the traditional user association approach, in which, each user is first assigned to the RRH with the largest average value of signal strength, and then, based on this fixed user association, front-haul link association and power allocation are optimized.

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“…The simulation results in Figs. 7a and 7b confirm the analytical analysis of computational complexity according to (13). Similarly, Figs.…”

Section: A Computational Complexitysupporting

confidence: 78%

Section: B Related Workmentioning

confidence: 99%

User Association in Cloud RANs with Massive MIMO

Parsaeefard

Jumba

Shoaei

et al. 2021

IEEE Trans. Cloud Comput.

View full text Add to dashboard Cite

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“…Without loss of generality, the three‐cell system model, such as in the works of Ho and Huang and Kim et al, is considered to catch the main features of multicell systems but make the problem relatively easy to manage. In the considered multicell systems, there are K mobile users that are uniformly distributed in each hexagonal cell.…”

Section: System Modelmentioning

confidence: 99%

High‐reliability and low‐complexity resource allocation for future multicarrier spread spectrum systems

Shi

Xiao

Liang

et al. 2018

Trans Emerging Tel Tech

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In this paper, we investigate resource allocation in the multicarrier spread spectrum systems, especially in the multicell downlink multicarrier direct‐sequence code division multiple‐access systems. The allocation of resources including subcarriers and spreading codes aims to maximize the system reliability, thereby resulting in the high‐reliability mutlicarrier systems. For the sake of achieving low complexity, we develop the novel resource allocation framework. We propose two resource allocation algorithms, which are the simplified heuristic subcarrier‐ and code‐allocation (SHSC) algorithm and the enhanced heuristic subcarrier‐ and code‐allocation (EHSC) algorithm. The two proposed algorithms can find the promising suboptimum solutions to the mixed integer nonconvex resource allocation problem. The SHSC algorithm has lower complexity and demands less backhaul resources than the EHSC algorithm. In return, the EHSC algorithm performs better than the SHSC algorithm. Nevertheless, we show that both algorithms significantly outperform the existing algorithms while approaching the optimal algorithm of high complexity.

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“…Moreover, in Algorithms 1.A and 1.B, for each iteration, the number of computations required to convert the nonconvex problems using AGMA into (15) and (22)…”

Section: Computational Complexitymentioning

confidence: 99%

Joint User-Association and Resource-Allocation in Virtualized Wireless Networks

et al. 2016

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In this paper, we consider a down-link transmission of multicell virtualized wireless networks (VWNs) where users of different service providers (slices) within a specific region are served by a set of base stations (BSs) through orthogonal frequency division multiple access (OFDMA). In particular, we develop a joint BS assignment, sub-carrier and power allocation algorithm to maximize the network throughput, while satisfying the minimum required rate of each slice. Under the assumption that each user at each transmission instance can connect to no more than one BS, we introduce the user-association factor (UAF) to represent the joint sub-carrier and BS assignment as the optimization variable vector in the mathematical problem formulation. Sub-carrier reuse is allowed in different cells, but not within one cell. As the proposed optimization problem is inherently non-convex and NP-hard, by applying the successive convex approximation (SCA) and complementary geometric programming (CGP), we develop an efficient two-step iterative approach with low computational complexity to solve the proposed problem. For a given power-allocation, Step 1 derives the optimum userassociation and subsequently, for an obtained user-association,Step 2 find the optimum power-allocation. Simulation results demonstrate that the proposed iterative algorithm outperforms the traditional approach in which each user is assigned to the BS with the largest average value of signal strength, and then, joint sub-carrier and power allocation is obtained for the assigned users of each cell. Especially, for the cell-edge users, simulation results reveal a coverage improvement up to 57% and 71% for uniform and non-uniform users distribution, respectively leading to more reliable transmission and higher spectrum efficiency for VWN.Index Terms-Complementary geometric programming, successive convex approximation, joint user association and resource allocation, virtualized wireless networks.

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Sum-Rate Maximization for Multicell OFDMA Systems

Cited by 23 publications

References 33 publications

User Association in Cloud RANs with Massive MIMO

User Association in Cloud RANs with Massive MIMO

High‐reliability and low‐complexity resource allocation for future multicarrier spread spectrum systems

Joint User-Association and Resource-Allocation in Virtualized Wireless Networks

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