Flexible Resource Allocation for Joint Optimization of Energy and Spectral Efficiency in OFDMA Multi-Cell Networks

Jing, Wenpeng; Lu, Zhaoming; Wen, Xiangming; Hu, Zhiqun; Yang, Shaoshi

doi:10.1109/lcomm.2015.2392113

Cited by 22 publications

(16 citation statements)

References 11 publications

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“…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%

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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Section: B Related Workmentioning

confidence: 99%

User Association in Cloud RANs with Massive MIMO

Parsaeefard

Jumba

Shoaei

et al. 2021

IEEE Trans. Cloud Comput.

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“…In the work of Jafarizadeh et al [21] it has been shown that the simulation in MS scenarios and usage of linear and random NC reduces latency. In the work of Jing et al [22] it has been shown that by simulation NC reduces the delay in downloading files compared to non-NC applications. Lohne and Weibing [23] illustrate that NC can be used on interactive mobile devices with multiple interfaces.…”

Section: Related Workmentioning

confidence: 99%

Increasing the amount of collected data using network coding and continuous movement of mobile sinks in wireless sensor networks

2020

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This study uses the network coding (NC) and mobile sinks (MSs) for collecting coded data (CCD) of sensor nodes (SNs). MSs move on a steady, direct and predetermined path with constant velocity in wireless sensor networks. The authors present an optimisation model for CCD problem which is a generalisation of the previous works and an optimisation model based on the integrated linear programming model. Solving this problem in polynomial time is not possible. In this model for CCD, each SN and MS are assigned a time slice, and two conditions are presented for transmission range of SNs and at most number time slices for CCD. Then a centralised algorithm with polynomial time complexity is presented in proposed conditions for the problem solving. Finally, by simulating, different sets of SNs are deployed randomly with a fixed position, which was evaluated by influence of the number of SNs, travelled distance of MS at each time slice, the duration of time slice, velocity of MS on delay, the total amount of CCD and network efficiency. The simulation results represent scalability and performance superiority of the proposed algorithm compared to methods with no NC such as C-Schedule and GAP-based approximation algorithms.

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“…However, less efforts have been devoted to the research of the energy-efficient multicell resource allocation. An iterative subchannel allocation and power allocation algorithm was proposed in [22] for joint optimization of energy and spectral efficiency. In [23], a distributed resource allocation scheme-based game theory, taking user fairness and priority into consideration, was proposed to solve the energy-efficient RA problem.…”

Section: Related Workmentioning

confidence: 99%

Energy-efficient multi-cell resource allocation in cognitive radio-enabled 5G systems

Yan

et al. 2019

EURASIP J. Adv. Signal Process.

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In this paper, we propose an energy-efficient resource allocation (RA) algorithm in cognitive radio-enabled 5th generation (5G) systems, where the scenario including one primary system and multiple secondary cells is considered. Because of the high spectrum leakage of traditional orthogonal frequency division multiplexing (OFDM), alternative modulation schemes regarded as the potential air interfaces in 5G are analyzed, e.g., filter bank-based multi-carrier (FBMC), generalized frequency division multiplexing (GFDM), and universal filtered multi-carrier (UFMC). Our objective is to maximize the whole energy efficiency of secondary system defined by the ratio of the capacity to the total power consumption subject to some practical constraints. The general formulation leads to a non-convex mixed-integer nonlinear programming problem with fractional structure, which is challenging to solve due to its intractability and significant complexity. Therefore, we resort to an alternate optimization framework to optimize the variables of subcarrier assignment and power allocation, where successive convex approximation (SCA) is employed so that the general formulation is finally transformed into a solvable convex problem. Numerical results validate the effectiveness of the proposed RA algorithm, and the comparison with some existing RA algorithms is conducted. In addition, the performance of using different 5G candidate waveforms in the energy-efficient RA algorithm is also presented and discussed.

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Flexible Resource Allocation for Joint Optimization of Energy and Spectral Efficiency in OFDMA Multi-Cell Networks

Cited by 22 publications

References 11 publications

User Association in Cloud RANs with Massive MIMO

User Association in Cloud RANs with Massive MIMO

Increasing the amount of collected data using network coding and continuous movement of mobile sinks in wireless sensor networks

Energy-efficient multi-cell resource allocation in cognitive radio-enabled 5G systems

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