On the Performance, Complexity, and Fairness of Suboptimal Resource Allocation for Multiuser MIMO–OFDMA Systems

Maciel, Tarcísio F.; Klein, Anja

doi:10.1109/tvt.2009.2029438

Cited by 63 publications

(76 citation statements)

References 29 publications

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“…Appendix C. Thus, under some mild conditions [22], it can be shown that strong duality holds and the duality gap is equal to zero. In other words, solving the dual problem is equivalent to solving the primal problem 7 .…”

Section: ) Sub-optimal Solution Of the Main Loop Problemmentioning

confidence: 99%

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

Lo²,

Schober

2012

IEEE Trans. Wireless Commun.

532

319

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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.

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Section: ) Sub-optimal Solution Of the Main Loop Problemmentioning

confidence: 99%

“…The combination of MIMO and OFDMA is considered a viable solution for achieving these high data rates [7], [8], [9]. In fact, the data rate improvement due to multiple antennas is unlimited if we allow the numbers of antennas employed at both the transmitter and the receiver to grow.…”

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.

532

319

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“…Our objective is to maximize the average sum rate while keeping fairness between the users by optimizing both the cluster and beam allocation [3,22],…”

Section: System Modelmentioning

confidence: 99%

“…It is also important to satisfy all users' requirements even if *Correspondence: berna.ozbek@cnam.fr CEDRIC/LAETITIA, CNAM, Paris, France the users are far from the base station (BS) by allocating the clusters and beams fairly. Therefore, not only the optimal set but also the fairness issue is considered by employing proportional fair scheduling algorithms (PFS) for MISO-OFDMA systems [3].…”

Section: Introductionmentioning

confidence: 99%

Feedback channel designs for fair scheduling in MISO–OFDMA systems

Özbek

Ruyet

2012

J Wireless Com Network

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In the next generation of wireless communication, adaptive resource allocation techniques will play an important role to improve quality of service and spectral efficiency. In order to employ adaptive fairness scheduling for multiple-input single-output (MISO) orthogonal frequency-division multiple access (OFDMA), the channel state information (CSI) belonging to all users is required at the base station. However, the amount of feedback increases with the number of users, transmit antennas and subchannels. Therefore, it is important to perform a user selection at the receiver side without cooperation among the users and to quantize the CSI. In this article, the reduced feedback channel designs are examined for MISO-OFDMA systems while providing fairness between the users. In order to reduce the feedback rate, we choose the users considering their norm and orthogonality properties as well as their location in the cell. In order to limit the feedback rate, channel direction information is quantized by designing a specific codebook thanks to the proposed criterion. We obtain an expression to determine the amount of required feedback information for MISO-OFDMA systems to support more than one beam per subchannel for a given number of users, subchannels and transmit antennas. The performance results of the reduced feedback channel designs are evaluated for fair scheduling in wireless channels.

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“…Resources can be considered as components of a 3 dimensional object where sub-carriers, Time-Slots (TS), and spatial layers correspond to frequency, time, and space resources, respectively [10]. In the Downlink (DL) sense, the Base Station (BS) decides which resource to be allocated to which Mobile Station (MS) based on Channel State Information (CSI) feedbacks.…”

Section: Introductionmentioning

confidence: 99%

A Recursive Resource Allocation Algorithm for MIMO-OFDMA Systems in Multi-user Context

Hassen¹,

Afif²,

Tabbane³

2012

IJCA

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This paper presents a new resource allocation algorithm for downlink multi-user MIMO-OFDMA systems. The main objective is to maximize the total system capacity and to guarantee the fairness among users with a low complexity. The proposed algorithm is based on a recursive sub-carriers allocation procedure aiming to satisfy Quality of Service (QoS) requirements for each mobile user. Simulation results demonstrate that the proposed algorithm performs well in terms of system capacity and fairness when the number of users in the cell is important closing to the practical case. General Terms4G technologies, wireless communication, optimization problem, Radio Resource Management (RRM).

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On the Performance, Complexity, and Fairness of Suboptimal Resource Allocation for Multiuser MIMO–OFDMA Systems

Cited by 63 publications

References 29 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

Feedback channel designs for fair scheduling in MISO–OFDMA systems

A Recursive Resource Allocation Algorithm for MIMO-OFDMA Systems in Multi-user Context

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