Adaptive Sub-Carrier and Bit Allocation Algorithms for Multi-User OFDM Wireless Systems

Orthogonal frequency division multiplexing (OFDM) is an optimal technique for high-speed transmission. In this paper, a multicell multiuser OFDM system with adaptive subcarrier allocation and adaptive modulation is considered. We propose an adaptive subcarrier, bit and power allocation algorithm to maximum the total throughput of the multicell system in the presence of cochannel interference (CCI), frequency selective Rayleigh fading and additive white Gaussian noise (AWGN). Its performance in a multicell system with different number of users is investigated through simulation. It is shown from the simulation that this adaptive allocation algorithm enhances the throughput of OFDM systems as compared to equal power allocation and is suitable for multiuser system.

This paper investigates the adaptive subcarrier and bit allocation algorithm for OFDMA systems. To minimize overall transmit power, we propose a novel adaptive subcarrier and bit allocation algorithm based on channel state information, Moreover, the block-wise method is considered based on channel variation for adaptive subcarrier and bit allocation. It is shown that a near optimal solution is obtained by the proposed algorithm which has low complexity compared to that of other conventional algorithms. Also, it is shown that the block-wise method significantly reduces the complexity and the feedback or side information though has a slight transmit power increase.

Multiuser orthogonal frequency division multiplexing (OFDM) is a very promising multiple access technique to efficiently utilize limited RF bandwidth and transmit power in wideband transmission over multipath fading channels. When a wideband spectrum is shared by multiple users in multiuser OFDM-based systems, different users may experience different fading conditions at all subcarriers. Each user is assigned a subset of all subcarriers by some allocation algorithm. Thus, multiuser diversity can be achieved by adaptively adjusting subcarrier, bit, and power allocation depending on channel status among users at different locations (Wong et al., 1999a). In (Wong et al., 1999a), Wong applies a Lagrangian optimization technique and an iterative algorithm to solve the subcarrier, bit and power allocation problem. The suboptimal scheme for the NP-hard joint optimization problem is decoupled into two steps while it has a high computational complexity. A sub-optimal algorithm has been proposed to solve a related problem (Wong et al., 1999b). In (Wong et al., 1999b), Wong presents a real-time subcarrier allocation (SA) algorithm. It is a two-phase algorithm, including the constructive initial assignment (CIA) and the subcarrier swapping steps. The initial subcarrier allocation algorithm needs to pre-determine the numbers of subcarriers for each user before the allocation process starts. The performance of the SAbased algorithm will be compared in the simulation. In (Kim et al., 2006), Kim shows that the allocation problem in (Wong et al., 1999a) can be transformed into an integer programming (IP) problem. The branch-and-bound algorithm (Wolsey, 1998) can be employed to find the optimal solution of the allocation problem which has exponential computational complexity in the worse cases. We utilize the approach to obtain the optimal solution as the performance bound for comparison. Evolutionary algorithms (EA) are used to solve extremely complex search and optimization problems which are difficult to solve through simple methods. EAs are intended to provide a better solution, as it is based on the natural theory of evolution. Evolutionary algorithm (EA)-based schemes have been applied to solve subcarrier, bit, and power allocation problems (Wang et al., 2005) (Reddy et al., 2007) (Reddy & Phora, 2007) (Pao & Chen, 2008). In general, chromosomes can be designed with binary, integer, or real representation. The chromosome lengths are related to the number of subcarriers. Each element in the chromosome is a subcarrier allocated to a user. In this research, a subset of subcarriers can be assigned to one user depending upon the availability of subcarriers at a particular time

In this paper, subcarrier and power allocation are jointly considered in a three-node symmetric cooperation orthogonal frequency-division multiple access uplink system. With the help of Nash bargaining solution, the dynamic subcarrier allocation scheme and the adaptive power allocation scheme are proposed for joint optimization. The joint resource allocation is decomposed and solved by dynamic subcarrier allocation algorithm and adaptive power allocation algorithm. Simulation results show the effectiveness of the proposed cooperative scheme.

In this paper, a dynamic resource allocation algorithm to satisfy the packet delay requirements for real-time services, while maximizing the system capacity in multiuser orthogonal frequency division multiplexing (OFDM) systems is discussed. Our proposed cross-layer algorithm, called Joint Dynamic Subcarrier Allocation and Flow Control (DSA-FC) algorithm, consists of two interactive components. In the medium access control (MAC) layer, the users' expected transmission rates in terms of the number of subcarriers per symbol and their corresponding transmission priorities are evaluated. With the subcarrier gain information of each user, the physical (PHY) layer subcarrier allocation is optimally designed to satisfy the users' requirements under the system signal-to-noise ratio (SNR) and power constraints. In a system where the number of active users changes dynamically, the MAC-layer congestion control and removal schemes can guarantee the quality of service (QoS) of the existing users in the system and fully utilize the bandwidth resource. The proposed algorithm combines these two components, and the numerical results show that it significantly improves the system performance in terms of the bandwidth efficiency and delay performance for real-time services.

The Modern Society is becoming more and more dependable on technological inventions and gadgets which are increasing on very fast rate, hence user demands for wireless communication are increasing but existing networks are not able to fulfil the high data rate requirement for such services. As high data rate wireless access can be supported by more bandwidth but due to spectral limitations, it is very expensive to increase. Hence the available bandwidth is needed to be used efficiently. Orthogonal Frequency Division Multiplexing (OFDM) has been explored as a promising interface technology to utilize the bandwidth effectively. In order to serve multiple user demands, one of the most sophisticated techniques, resource allocation technique can be integrated into the OFDMA system. For achieving higher spectral efficiency and better Quality of Service (QoS) such as capacity and Bit Error Rate (BER) a combination of MIMO and OFDMA can be used. The present paper aims at developing a MIMO-OFDMA system for downlink transmission within one single cell. As an optimization method, subcarrier allocation is used for resource allocation. Eigen Value Decomposition (EVD) is used to decompose the MIMO channel into parallel single channels. On the basis of priority of user, subcarrier selection is done by using dominant eigen channels. By comparing the static allocation method (equal subcarrier allocation with equal power) and adaptive allocation methods (adaptive subcarrier allocation with equal power) the performance of the system is evaluated.

Utility function based fair data scheduling algorithm for OFDM wireless network

An important issue of supporting multi-users with diverse quality-of-service (QoS) requirements over wireless networks is how to optimize the systematic scheduling by intelligently utilizing the available network resource while, at the same time, to meet each communication service QoS requirement. In this work, we study the problem of a variety of communication services over multi-media heterogeneous cognitive OFDM system. We first divide the communication services into two parts. Multimedia applications such as broadband voice transmission and real-time video streaming are very delay-sensitive (DS) and need guaranteed throughput. On the other side, services like file transmission and email service are relatively delay tolerant (DT) so varying-rate transmission is acceptable. Then, we formulate the scheduling as a convex optimization problem, and propose low complexity distributed solutions by jointly considering channel assignment, bit allocation, and power allocation. Unlike prior works that do not care computational complexity. Furthermore, we propose the FAASA (Fairness Assured Adaptive Sub-carrier Allocation) algorithm for both DS and DT users, which is a dynamic sub-carrier allocation algorithm in order to maximize throughput while taking into account fairness. We provide extensive simulation results which demonstrate the effectiveness of our proposed schemes.

SUMMARYIn this paper we study the resource allocation problem for the multiuser orthogonal frequency division multiplexing (OFDM)‐based cognitive radio (CR) systems with proportional rate constraints. The mutual interference introduced by primary user (PU) and cognitive radio user (also referred to secondary user, SU) makes the optimization problem of CR systems more complex. Moreover, the interference introduced to PUs must be kept under a given threshold. In this paper, the highest achievable rate of each OFDM subchannel is calculated by jointly considering the channel gain and interference level. First, a subchannel is assigned to the SU with the highest achievable rate. The remaining subchannels are always allocated to the SU that suffers the severest unjustness. Second, an efficient bit allocation algorithm is developed to maximize the sum capacity, which is again based on the highest achievable rate of each subchannel. Finally, an adjustment procedure is designed to maintain proportional fairness. Simulation results show that the proposed algorithm maximizes the sum capacity while keeping the proportional rate constraints satisfied. The algorithm exhibits a good tradeoff between sum capacity maximization and proportional fairness. Furthermore, the proposed algorithm has lower complexity compared with other algorithms, rendering it promising for practical applications. Copyright © 2011 John Wiley & Sons, Ltd.

The adaptive subcarrier and bit allocation in OFDMA systems supporting multiple services is investigated. A suboptimal algorithm is developed, which aims to maximize the system throughput under the overall transmit power constraint while guaranteeing the QoS requirement of realtime users and supporting proportional fairness among non-realtime users. Firstly, the algorithm allocates subcarriers and power to realtime users so that the required power for them is minimized and the average power per subcarrier of realtime users is approximately equal to that of non-realtime users. Then, the remaining subcarriers and power are allocated to non- realtime users by a proposed rate adaptive resource allocation algorithm, which achieves a suboptimal overall throughput while providing proportional fairness among users. Simulation results show that the proposed algorithm achieves better performances than existing algorithms.

Link adaptation technique is applied in an amplify and forward (AF) - orthogonal frequency division multiplexing (OFDM) relaying system, and adaptive bit and power allocation (ABPA) is investigated for such system. ABPA problem is presented first, and the optimal solution is proposed with aid of Greedy algorithm. Because channel transfer functions for two hops are independent, which limits throughput of a conventional AF-OFDM system, we take sub-carrier coupling (SQ into account. Two solutions are proposed for the problem with ABPA and SC; the first adopts a concatenated method to realize SC and ABPA with two steps, and the second utilized a joint way to adjust SC and allocated bits and power. Numeral simulation results show that the proposed ABPA solution can improve throughput greatly while guaranteeing bit error rate (BER) requirement very well. When SC is involved, more improvement can be obtained; the joint solution outperforms the concatenated solution.

Multi-User Orthogonal Frequency Division Multiplexing (MU-OFDM) is an efficient technique for achieving high downlink capacity in high-speed communication systems. A key issue in MU-OFDM is the allocation of the OFDM subcarriers and power to users sharing the channel. In this paper a proportional rate-adaptive resource allocation algorithm for MU-OFDM is presented. Subcarrier and power allocation are carried out sequentially to reduce the complexity. The low complexity proportional subcarriers allocation is followed by Greedy Power Allocation (GPA) to solve the rate-adaptive resource allocation problem with proportional rate constraints for MU-OFDM systems. It improves the work of Wong et al. in this area by introducing an optimal GPA that achieves approximate rate proportionality, while maximizing the total sum-rate capacity of MU-OFDM. It is shown through simulation that the proposed GPA algorithm performs better than the algorithm of Wong et al., by achieving higher total capacities with the same computational complexity, especially, at larger number of users and roughly satisfying user rate proportionality.

This paper investigates a multi-cell communication technique for OFDM (Orthogonal Frequency Division Multiplexing)-based asynchronous networks without the use of a GPS (Global Positioning System). First, a downlink macro-diversity technique using bandwidth division allocation is presented, where each MS (Mobile Station) simultaneously receives control information from surrounding BSs (Base Stations) using an FFT (Fast Fourier Transform) module. Second, a hierarchical master-slave synchronization technique is introduced for plug & access network synchronization. Finally, an adaptive guard carrier allocation scheme is proposed to reduce the effect of MAI (Multiple Access Interference) for users receiving multiple transmission signals from surrounding BSs. In a simulation, the proposed technique is well designed to achieve SSDT (Site Selection Diversity Transmission) and adaptive synchronization for OFDM-based networks. It is particularly noteworthy that this adaptive sub-carrier allocation is very effective in reducing MAI for plug and access network synchronization.

We consider the sum rate maximization problem in downlink OFDMA systems subject to total transmit power and minimum user rate constraints. A low complexity suboptimal resource allocation algorithm is proposed for joint optimization of multiuser subcarrier assignment and power allocation. The algorithm is based on Lagrangian relaxation where the non-convex optimization problem is decomposed into a master problem and a subproblem. Subproblem has a similar form as standard weighted sum rate maximization subject to total transmit power. Standard subgradient method is used in the master problem and a suboptimal algorithm inspired from primal decomposition techniques is also proposed to approximately solve the subproblem. Simulations are provided to compare the performance of the proposed algorithm to fixed spectrum assignment based algorithms with adaptive power control.

In this paper, a concept of utility proportional fairness is defined, which achieves fairness of utility for different applications. The optimization problem of utility proportional fairness has been formulated meanwhile the optimal solution is presented. The utility proportional fairness is applied in the orthogonal frequency division multiplexing (OFDM) wireless networks, and the optimal subcarrier allocation for utility proportional fairness is deduced. An effective and practical simplified subcarrier allocation algorithm is proposed, in which the instantaneous data rate is substituted by average rate via exponentially weighted low pass time window. Simulation results illustrate that both the optimal and simplified subcarrier allocation algorithms guarantee the utility fairness between different applications well, and the simplified algorithm achieves a perfect tradeoff between utility fairness and system throughput and provides the quality of server (QoS) for multimedia applications.