Transmit Power Allocation for BER Performance Improvement in Multicarrier Systems

Park, Chang Soon; Lee, Kwang Bok

doi:10.1109/tcomm.2004.836491

Cited by 78 publications

(69 citation statements)

References 9 publications

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“…In [17] optimal power allocation by steepest descent algorithm is introduced. In the beginning initial power to each carrier (p m (0)) and initial step size parameter µ(0) are set.…”

Section: Adaptive Power Allocationmentioning

confidence: 99%

“…In the beginning initial power to each carrier (p m (0)) and initial step size parameter µ(0) are set. The power is updated accordingly as [17]:…”

Section: Adaptive Power Allocationmentioning

confidence: 99%

“…Otherwise the stepsize on specific carrier m with negative p m is updated. The new µ m becomes [17]: (10) and the new stepsize µ(i) becomes the multiplication of a scaling factor ρ(0 < ρ < 1) with the smallest µ m [17]. The power to those carriers (p m ) is updated again according to (8) until all p m s are nonnegative and P T constraint is achieved.…”

Section: Adaptive Power Allocationmentioning

confidence: 99%

“…A suboptimal power allocation is also introduced in [17] by utilizing the upper bound approximation of the BER function (v()) as:…”

Section: Adaptive Power Allocationmentioning

confidence: 99%

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Cognitive Radio Dynamic Access Techniques

Budiarjo

Лакшманан

Nikookar

2008

Wireless Pers Commun

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The ever growing demand for wireless services has placed enormous burden on valuable resources such as spectral bandwidth. This has resulted in a major rethinking in resource allocation policies culminating in an explosion of research activity in the field of Cognitive Radio (CR) towards optimum resource usage. In this tutorial paper the physical layer design and transmission techniques for CR in the context of efficient spectrum utilization are discussed. Spectrum sensing as the key element of CR awareness is described. Orthogonal frequency division multiplexing (OFDM) as a spectrally efficient modulation scheme is discussed and the rationale for its use in the CR system is explained. Spectrum pooling for efficient use of spectrum is studied and the role of adaptive OFDM techniques in this method is highlighted. Wavelet basis function as a replacement of Fourier transform in OFDM is evaluated. MIMO system as an added value to the CR performance is described. Adaptive Waveform and beamforming as alternative techniques in CR are reviewed.

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“…In [17] optimal power allocation by steepest descent algorithm is introduced. In the beginning initial power to each carrier (p m (0)) and initial step size parameter µ(0) are set.…”

Section: Adaptive Power Allocationmentioning

confidence: 99%

“…In the beginning initial power to each carrier (p m (0)) and initial step size parameter µ(0) are set. The power is updated accordingly as [17]:…”

Section: Adaptive Power Allocationmentioning

confidence: 99%

Section: Adaptive Power Allocationmentioning

confidence: 99%

“…A suboptimal power allocation is also introduced in [17] by utilizing the upper bound approximation of the BER function (v()) as:…”

Section: Adaptive Power Allocationmentioning

confidence: 99%

See 2 more Smart Citations

Cognitive Radio Dynamic Access Techniques

Budiarjo

Лакшманан

Nikookar

2008

Wireless Pers Commun

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“…In general, cognitive wireless radio network is capable to adapt to the outside existing time varying environment. According to the descriptions in [1], the power control has an effective impact on the probability of bit error rate. In [2] joint beamforming and power control using weighted least square algorithm have been performed.…”

Section: Introductionmentioning

confidence: 99%

Bio-inspired distributed beamforming for cognitive radio networks in non-stationary environment

Derakhshan-Barjoei

Dadashzadeh

Razzazi

et al. 2011

IEICE Electron. Express

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Distributed power control by beamforming approach in cognitive radio networks requires a precise analysis of the impacts of the transmission parameters, tolerable interference and guarantees the quality of service of both the primary users and secondary users. In this paper, we propose an improved performance to solve the constrained nonlinear multi-object optimization and coherent power assignment by beamforming problem based on particle swarm optimization. This method is invoked to solve the constrained nonlinear optimization problem in order to reach to maximum capacity. A numerical study is performed to show the convergence behavior of the proposed algorithm and the efficiency of the proposed technique with a dynamic cost function.

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Power distribution methods for MIMO‐OFDM systems and field experimentations

Bocquet

Hayashi

Sakai

2009

Wireless Communications

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In this paper, we propose several power allocation schemes for multi‐input multi‐output (MIMO) orthogonal frequency division multiplexing (OFDM) transmission based on the minimization of an approximated bit error rate (BER) expression, and we evaluate the different solutions via field trial experimentations. The methods illustrated in this paper, serve to allocate power among the different transmit antennas and the different subcarriers which compose the MIMO OFDM transmitted signal. Several solutions are available to perform power allocation. Frequency domain power allocation, spatial domain power allocation and combined spatial and frequency power allocation are evaluated. We first review and describe the analytical solution for each power allocation scheme and then evaluate the complexity in terms of both computational operations and BER performances. Simulation results show the performance in term of BER and link the advantage of each possibility of power distribution with the associated complexity. Copyright © 2009 John Wiley & Sons, Ltd.

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Transmit Power Allocation for BER Performance Improvement in Multicarrier Systems

Cited by 78 publications

References 9 publications

Cognitive Radio Dynamic Access Techniques

Cognitive Radio Dynamic Access Techniques

Bio-inspired distributed beamforming for cognitive radio networks in non-stationary environment

Power distribution methods for MIMO‐OFDM systems and field experimentations

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