Adaptive Subcarrier Assignment Research Articles

Advanced ADO-OFDM With Adaptive Subcarrier Assignment and Optimized Power Allocation

Visible light communication (VLC) is emerging as a promising technology thanks to the superior advantages of light-emitting diodes. In this letter, an advanced asymmetrically clipped dc biased optical orthogonal frequency division multiplexing (AADO-OFDM) scheme with adaptive subcarrier assignment is proposed to accommodate the demands of multi-users. Additionally, the optimization of optical power allocation for AADO-OFDM under the constrained total optical power is investigated and formulated to maximize the tight lower bound of the total channel capacity. Simulation results show that compared with the schemes without optimal power allocation, the proposed scheme can maximize the lower bound of channel capacity.

Joint Optimal Subcarrier and Power Allocation for Wireless Cooperative Networks Over OFDM Fading Channels

In this paper, we consider the adaptive subcarrier assignment and fair power control strategy that minimize a cost function of average relay powers for multiuser wireless orthogonal frequency-division multiplexing (OFDM) networks, where a set of relays assists communication between sources and destinations with an amplify-and-forward strategy. Using a class of β-fair cost functions to balance the tradeoff between energy efficiency and fairness, joint optimal subcarrier and power-allocation schemes at the relays are derived in a quasi-closed form. In addition, we develop novel stochastic algorithms capable of dynamically learning the intended wireless channels on the fly to approach the optimal policy. Numerical results are provided to evaluate the proposed schemes for multiuser OFDM relay networks over block-fading channels.

Impact of CSI on Radio Resource Management Techniques for the OFDMA downlink

Adaptive resource allocation can drastically increase the throughput of an Orthogonal Frequency Division Multiple Access (OFDMA) system when the Channel State Information (CSI) is accurately known. Unfortunately, in practice, perfect CSI is rarely possible. In this paper, we consider adaptive sub-carrier assignment for downlink multiuser OFDMA systems, where the transmitter has no knowledge of the instantaneous channel realizations. The problem we address is maximizing the sum-capacity of the system subject to user Quality of Service (QoS) requirements. A heuristic algorithm presented in \cite{Zhang06} is modified in order to provide an enhanced sub-optimal solution. Numerical results show that resources can be adaptively allocated using statistical CSI (SCSI) and that such an approach allows for an important number of user QoS requirements to be met. Comparisons between the instantaneous CSI (ICSI) and SCSI based resource allocation schemes demonstrate that their performance difference is highly dependent on the number of active users present in the cell, the QoS constraint, and the transmit power.

A Computationally Efficient Method for Large Dimension Subcarrier Assignment and Bit Allocation Problem of Multiuser OFDM System

In this paper, we propose a computationally efficient method to solve the large dimension Adaptive Subcarrier Assignment and Bit Allocation (ASABA) problem of multiuser orthogonal frequency division multiplexing system. Our algorithm consists of three Ordinal Optimization (OO) stages to find a good enough solution to the considered problem. First of all, we reformulate the considered problem to separate it into subcarrier assignment and bit allocation problem such that the objective function of a feasible subcarrier assignment pattern is the corresponding optimal bit allocation for minimizing the total consumed power. Then in the first stage, we develop an approximate objective function to evaluate the performance of a subcarrier assignment pattern and use a genetic algorithm to search through the huge solution space and select s best subcarrier assignment patterns based on the approximate objective values. In the second stage, we employ an off-line trained artificial neural network to estimate the objective values of the s subcarrier assignment patterns obtained in stage 1 and select the l best patterns. In the third stage, we use the exact objective function to evaluate the l subcarrier assignment patterns obtained in stage 2, and the best one associated with the corresponding optimal bit allocation is the good enough solution that we seek. We apply our algorithm to numerous cases of large-dimension ASABA problems and compare the results with those obtained by four existing algorithms. The test results show that our algorithm is the best in both aspects of solution quality and computational efficiency.

Adaptive Subcarrier Assignment and Bit Allocation for Multiuser OFDM System Using Ordinal Optimization Approach

In this paper, we propose an ordinal optimization (OO) theory-based four-stage approach to deal with the subcarrier assignment and bit allocation problem of a multiuser orthogonal frequency-division multiplexing (OFDM) system. The four-stage OO approach ensures the quality of the obtained solution, however, at the cost of solving a continuous version of the considered problem in the first stage. To resolve this computational complexity problem, we propose a hardware-implementable dual projected gradient (DPG) method to exploit deep-submicrometer technology. Compared to some existing methods using numerous simulation cases with randomly generated parameters, our approach is excellent in the aspect of power consumption. In the meantime, the estimated computation time of our approach can meet the real-time application requirement. Furthermore, we use extensive simulations to compare our good-enough solutions with the true optimal solutions, and the results show that the objective value obtained by our approach deviates from the optimal objective value around 1% on average.