Energy-efficient resource allocation in wireless OFDMA systems

Akbari, Amir; Hoshyar, Reza; Tafazolli, Rahim

doi:10.1109/pimrc.2010.5671913

Cited by 49 publications

(30 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [10], a power loading algorithm is designed to minimize the energy-per-goodbit of a MIMO system. In [11] and [12], power allocation algorithms for energy-efficient multi-carrier systems were studied for macro-cell and hybrid cell structures, respectively. In 1536-1276/12$31.00 c 2012 IEEE [14] and [15], energy-efficient link adaptation for a linear sum rate-dependent dynamic circuit power consumption was considered.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Resource Allocation in OFDMA Systems with Large Numbers of Base Station Antennas

Lo²,

Schober

2012

IEEE Trans. Wireless Commun.

526

319

View full text Add to dashboard Cite

In this paper, resource allocation for energy-efficient communication in an orthogonal frequency division multiple access (OFDMA) downlink network with a large number of transmit antennas is studied. The considered problem is modeled as a non-convex optimization problem which takes into account the circuit power consumption, imperfect channel state information at the transmitter (CSIT), and different quality of service (QoS) requirements including a minimum required data rate and a maximum tolerable channel outage probability. The power allocation, data rate adaptation, antenna allocation, and subcarrier allocation policies are optimized for maximization of the energy efficiency of data transmission (bit/Joule delivered to the users). By exploiting the properties of fractional programming, the resulting non-convex optimization problem in fractional form is transformed into an equivalent optimization problem in subtractive form, which leads to an efficient iterative resource allocation algorithm. In each iteration, the objective function is lower bounded by a concave function which can be maximized by using dual decomposition. Simulation results illustrate that the proposed iterative resource allocation algorithm converges in a small number of iterations and demonstrate the trade-off between energy efficiency and the number of transmit antennas.Index Terms-Energy efficiency, green communication, multiuser MIMO, large numbers of antennas, resource allocation.

show abstract

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Resource Allocation in OFDMA Systems with Large Numbers of Base Station Antennas

Lo²,

Schober

2012

IEEE Trans. Wireless Commun.

526

319

View full text Add to dashboard Cite

show abstract

“…In [7], a power loading algorithm was proposed to maximize the EE of MIMO. In [8], the authors investigated the energy-efficient bandwidth allocation in downlink flat fading OFDMA channels and maximized the numbers of bits transmitted per joule, by using the Lagrangian and time-sharing techniques. In [9], the authors proposed a hybrid structure of resource allocation in OFDMA cellular systems, which maximized both the EE and the downlink system capacity.…”

Section: Introductionmentioning

confidence: 99%

Fog Computing‐Assisted Energy‐Efficient Resource Allocation for High‐Mobility MIMO‐OFDMA Networks

Wang

et al. 2018

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

This paper presents a suboptimal approach for resource allocation of massive MIMO-OFDMA systems for high-speed train (HST) applications. An optimization problem is formulated to alleviate the severe Doppler effect and maximize the energy efficiency (EE) of the system. We propose to decouple the problem between the allocations of antennas, subcarriers, and transmit powers and solve the problem by carrying out the allocations separately and iteratively in an alternating manner. Fast convergence can be achieved for the proposed approach within only several iterations. Simulation results show that the proposed algorithm is superior to existing techniques in terms of system EE and throughput in different system configurations of HST applications.

show abstract

“…In [10], a time-averaged bit/J metric was used to build a low-complexity scheme in multiuser OFDMA uplink system. Based on the OFDMA flat channel downlink system, the number of subcarriers and power were allocated for each user accordingly in [11] to maximise the transmit rate supported by 1 J energy consumption. In conclusion, the research on the energy-efficiency problem in traditional wireless system without relays has obtained some achievements.…”

Section: Introductionmentioning

confidence: 99%

Energy‐efficient adaptive power allocation in orthogonal frequency division multiplexing‐based amplify‐and‐forward relay link

2013

View full text Add to dashboard Cite

Recently, improving energy efficiency has been a new tendency in wireless relay communication. However, the introduction of relay technology may increase the system capacity, but is often followed by a more severe energy-efficiency problem when compared with traditional single-hop system. In this study, based on orthogonal frequency division multiplexing-based frequency-selective channel of amplify-and-forward relay link, a suboptimal two-step power allocation algorithm of subcarriers is proposed to maximise the energy efficiency. The proposal includes two steps. First, a suboptimal subcarrier matching is achieved for introducing a virtual direct link, which may reduce the dimensionality of the power allocation. Second, the allocation problem of relay network is simplified as that in traditional cellular network. Thus, the optimal power allocation of virtual direct link can be obtained by one-dimensional search method. Furthermore, the effects of rate and power constraints on the energy-efficiency problem are analysed. Simulation shows that the suboptimal solution of the proposed algorithm is very close to the optimal solution, and the proposed energy efficient power allocation method can achieve the highest energy efficiency, compared with the rate adaptive and margin adaptive optimisations.

show abstract

Energy-efficient resource allocation in wireless OFDMA systems

Cited by 49 publications

References 12 publications

Energy-Efficient Resource Allocation in OFDMA Systems with Large Numbers of Base Station Antennas

Energy-Efficient Resource Allocation in OFDMA Systems with Large Numbers of Base Station Antennas

Fog Computing‐Assisted Energy‐Efficient Resource Allocation for High‐Mobility MIMO‐OFDMA Networks

Energy‐efficient adaptive power allocation in orthogonal frequency division multiplexing‐based amplify‐and‐forward relay link

Contact Info

Product

Resources

About