Adaptive Subcarrier Allocation Research Articles

Genetic Algorithm Dependent Qos Aware Adaptive Subcarrier Allocation Scheme in Cognitive Radio Networks

Cognitive Radio Network technology is an efficient and intelligent system with the intention of detecting automatically about the availability of channels in a wireless spectrum and changing transmission parameters to facilitate more communication.In Quality of Service aware spectrum decision making system is locating the spectrum bands all the way through in view of the application necessities by means of the self-motivated nature of the spectrum bands.Here, an innovative adaptive sub-carrier allocation mechanism is proposed for Cognitive Radio Networks by rearranging the functional parameters anchored in the Proportional Resource Algorithm and Genetic Algorithm.This proposed scheme is designed to achieve a divergent performance standard for subcarrier allocation and power allocation system of the Cognitive Radio Network users. The suggested scheme is proven to be effective by maximizing the allocation of data rate for each subcarrier. Moreover, by increasing the overall network throughput, the numbers of satisfied users within bandwidth limits are maintained with the quality of service. In fact, it locates the maximum channel availability.

Efficient Resource Allocation in Device-to-Device Communication Using Cognitive Radio Technology

Device-to-device (D2D) communication is developed as a new paradigm to enhance network performance according to LTE and WiMAX advanced standards. The D2D communication may have dedicated spectrum (overlay) or shared spectrum (underlay). However, the allocated dedicated spectrum may not be effectively used in the overlay mode, while interference between the D2D users and cellular users cause impairments in the underlay mode. Can the resource allocation of a D2D system be optimized using the cognitive approach where the D2D users opportunistically access the underutilized radio spectrum? That is the focus of this paper. In this paper, the transmission rate of the D2D users is optimized while simultaneously satisfying five sets of constraints related to power, interference, and data rate, modeling D2D users as cognitive secondary users. Furthermore, a two-stage approach is considered to allocate the radio resources efficiently. A new adaptive subcarrier allocation scheme is designed first, and then, a novel power allocation scheme is developed utilizing geometric water-filling approach that provides optimal solution with low computation complexity for this nonlinear problem. Numerical results show that the proposed approach achieved significant performance enhancement than the existing schemes.

Multimedia transmission in MC-CDMA using adaptive subcarrier power allocation and CFO compensation

ABSTRACTMulticarrier code division multiple access (MC-CDMA) system is one of the most effective techniques in fourth-generation (4G) wireless technology, due to its high data rate, high spectral efficiency and resistance to multipath fading. However, MC-CDMA systems are greatly deteriorated by carrier frequency offset (CFO) which is due to Doppler shift and oscillator instabilities. It leads to loss of orthogonality among the subcarriers and causes intercarrier interference (ICI). Water filling algorithm (WFA) is an efficient resource allocation algorithm to solve the power utilisation problems among the subcarriers in time-dispersive channels. The conventional WFA fails to consider the effect of CFO. To perform subcarrier power allocation with reduced CFO and to improve the capacity of MC-CDMA system, residual CFO compensated adaptive subcarrier power allocation algorithm is proposed in this paper. The proposed technique allocates power only to subcarriers with high channel to noise power ratio. The performance of the proposed method is evaluated using random binary data and image as source inputs. Simulation results depict that the bit error rate performance and ICI reduction capability of the proposed modified WFA offered superior performance in both power allocation and image compression for high-quality multimedia transmission in the presence of CFO and imperfect channel state information conditions.

Power allocation and subcarrier assignment for joint delivery of unicast and broadcast transmissions in OFDM systems

Most existing studies on broadcast services in orthogonal frequency division multiplexing (OFDM) systems have focused on how to allocate the transmission power to the subcarriers. However, because a broadcasting system must guarantee quality of service to all users, the performance of the broadcast service dominantly depends on the channel state of the user who has the lowest received signal-to-noise ratio among users. To reduce the effect of the worst user on the system performance, we propose a joint delivery scheme of unicast and broadcast transmissions in OFDM systems with broadcast and unicast best-effort users. In the proposed joint delivery scheme, the BS delivers the broadcast information using both the broadcast and unicast subcarriers at the same time in order to improve the performance of the broadcast service. The object of the proposed scheme is to minimize the outage probability of the broadcast service while maximizing the sum-rate of besteffort users. For the proposed joint delivery scheme, we develop an adaptive power and subcarrier allocation algorithm under the constraint of total transmission power. This paper shows that the optimal power allocation over each subcarrier in the proposed scheme has a multi-level water filling form. Because the power allocation and the subcarrier assignment problems should be jointly solved, we develop an iterative algorithm to find the optimal solution. Numerical results show that the proposed joint delivery scheme with adaptive power and subcarrier allocation outperforms the conventional scheme in terms of the outage probability of the broadcast service and the sum-rate of best-effort users.

Adaptive OFDMA with partial CSI for downlink underwater acoustic communications

Multiuser communication has been an important research area of underwater acoustic communications and networking. This paper studies the use of adaptive orthogonal frequencydivision multiple access (OFDMA) in a downlink scenario, where a central node sends data to multiple distributed nodes simultaneously. In practical implementations, the instantaneous channel state information (CSI) cannot be perfectly known by the central node in time-varying underwater acoustic (UWA) channels, due to the long propagation delays resulting from the low sound speed. In this paper, we explore the CSI feedback for resource allocation. An adaptive power-bit loading algorithm is presented, which assigns subcarriers to different users and allocates power and bits to each subcarrier, aiming to minimize the bit error rate (BER) under power and throughput constraints. Simulation results show considerable performance gains due to adaptive subcarrier allocation and further improvement through power and bit loading, as compared to the non-adaptive interleave subcarrier allocation scheme. In a lake experiment, channel feedback reduction is implemented through subcarrier clustering and uniform quantization. Although the performance gains are not as large as expected, experiment results confirm that adaptive subcarrier allocation schemes based on delayed channel feedback or long term statistics outperform the interleave subcarrier allocation scheme.

Genetic Algorithm Based QoS Aware Adaptive Subcarrier Allocation in Cognitive Radio Networks

In this paper, an adaptive subcarrier allocation scheme with reconfiguration of operating parameters for Cognitive Radio Networks (CRN) is presented. A QoS-conscious spectrum decision frame work is projected, where spectrum bands are determined by considering the application requirements as well as the dynamic nature of the spectrum bands. The novel subcarrier allocation algorithm is developed to fulfill different performance objective as a solution for subcarrier allocation and power allocation problem for Cognitive Radio (CR) users in CRNs. It employs operating frequency parameter modification using Proportional Resource Algorithm and Genetic Algorithm (GA). The multi objective optimization problem with equality and inequality constraint is considered. Moreover, a dynamic subcarrier allocations scheme is developed based on GA to decide on the spectrum bands adaptively dependent on the time-varying CR network capacity. The proposed algorithm targets to achieve maximum data rate for each subcarrier, maximize the overall network throughput and maximize the number of satisfied user under the constraints of bandwidth and guarantee Quality of Service (QoS) requirement from dynamic spectrum management (DSM) perspective. Moreover, it determines the best available channel.

QoS-Constrained Resource Allocation Scheduling for LTE Network

The goal of LTE (Long Term Evolution) is to provide high data transmission rate, scalable bandwidth, low latency, high-mobility, etc. LTE employs OFDM (Orthogonal Frequency Division Multiplexing) and SC-FDMA (Single Carrier - Frequency Division Multiple Access) for downlink and uplink data transmission, respectively. As to SC-FDMA, there are two constraints in doing resource allocation. First, the allocated resource blocks (RBs) should be contiguous. Second, those of the allocated RBs are forced to use the same modulation technique. The aim of this research is to propose a QoS-constraint resource allocation scheduling to enhance data transmission for uplink SC-FDMA. The proposed scheduling is a three-stage approach. In the first stage, it uses a time domain scheduler to differentiate user equipment (UE) services according to their distinct QoS service requirements. In the second stage, it uses a frequency domain scheduler to prioritize UE services based on channel quality. In the third stage, it limits the number of times of modulation downgrade of RBs allocation in order to enhance system throughput. In the simulations, the proposed method is compared to fixed sub-carrier dynamic resource allocation method and adaptive dynamic sub-carrier resource allocation method. Simulation results show that the proposed method outperforms the other two methods in terms of throughput, transmission delay, packet loss ratio, and RB utilization.

Adaptive Resource Allocation Algorithms for Multi-user MIMO-OFDM Systems

Radio resource allocation to the system users is the key challenge issue in multi-user orthogonal frequency division multiplexing (MU-OFDM) systems. In this paper, an efficient and low-complexity proportional rate-adaptive radio resource (sub-carrier and power) allocation algorithm for MU-OFDM is proposed to maximize the sum-rate capacity of the system and achieve acceptable users' rates fairness. Three-dimensional (spatial, frequency, and multi-user) greedy power allocation (GPA) algorithms for the MU multi-input multi-output OFDM (MU MIMO-OFDM) systems are proposed. The proposed algorithms start with spatial sub-carrier allocation followed by an optimal two-dimensional spatial-frequency GPA (SFGPA) step, which exploits both the spatial and frequency diversities. Therefore, spatial, frequency, and multi-user diversities are exploited by the proposed three-dimensional GPA algorithms. Several experiments are carried out to test the performance of the proposed three-dimensional GPA algorithms in terms of sum-rate capacity. The optimal solution is achieved by the three-dimensional dynamic sub-carrier-SFGPA with average gain (DS-SFGPA-AG) algorithm, which achieves the best sum-rate capacity performance compared with the other power allocation algorithms. The performance of the DS-SFGPA-AG algorithm is also analyzed and compared for the four OFDM-based systems; single-user (SU) OFDM, SU MIMO-OFDM, MU OFDM, and MU MIMO-OFDM. The MU MIMO-OFDM system with adaptive sub-carrier and power allocation outperforms the other systems.

CAPACITY IMPROVEMENT OF MIMO-OFDMA SYSTEM USING ADAPTIVE RESOURCE ALLOCATION ALGORITHM

The user demands for wireless communication are increasing but the existing networks are not able to fulfill the high data rate of future communication services. More bandwidth can support high data rate wireless access. Due to spectral limitations, it is very expensive to increase. Therefore, the available bandwidth is needed to use efficiently. Orthogonal Frequency Division Multiplexing (OFDM) has been explored as a promising air interface technology to utilize the bandwidth effectively. OFDM can be exploited as a multiple access technique, called Orthogonal Frequency Division Multiple Access (OFDMA) that can support both frequency and multiuser diversity. In order to serve the user population, one of the most sophisticated techniques, resource allocation technique, can be integrated into the OFDMA system. Multiple Input Multiple Output (MIMO) technology can increase the spectral efficiency because multiple data streams can be simultaneously transmitted over the channel. The combination of MIMO technology and OFDMA system can achieve both higher spectral efficiency and better Quality of Service (QoS) such as capacity, fairness, and Bit Error Rate (BER). In this paper, a MIMO-OFDMA system is developed for downlink transmission within one single cell. Two optimization methods such as subcarrier allocation and power allocation are used for resource allocation. To decompose the MIMO channel into parallel single channels, Eigen Value Decomposition (EVD) is used. Subcarrier selection is based on the priority of the user by using the dominant eigen channels. Water-filling algorithm is adapted for power distribution among users. The aim is to maximize the system capacity subject to constraints on total power and proportional fairness. The performance of the system is evaluated by comparing the static allocation method (equal subcarrier allocation with equal power) and two adaptive allocation methods (adaptive subcarrier allocation with equal power and adaptive subcarrier allocation with adaptive power).

Aadptive Subcarrier Allocation for Multiple Cognitive Users over Fading Channels

In Cognitive Radio Network (CRN), where Primary User (PU) and multiple Secondary Users (SUs) wish to communicate with their corresponding receivers simultaneously over fading channels, spectrum utilization and efficient resource allocation are both significant points for CRN. Interference between PU and SUs should be eliminated in order to realize spectrum sharing. Multi-user resource allocation with the target of maximizing the spectral efficiency of SUs and satisfying the proportional rate constraint between SUs are proposed under the conditions of total SU interference constraint. An adaptive low-complexity suboptimal algorithm for subcarrier and power joint allocation is presented based on Rate Adaptive (RA) criterion, where adaptive subcarrier allocation is performed by assuming equal power distribution, while each subcarrier is assigned in accordance with subcarrier efficiency function. Moreover, linear water-filling algorithm for power allocation is applied within each subcarrier. Simulation results indicate that, with the proposed adaptive subcarrier allocation, spectral efficiency of multiple SUs is superior to traditional subcarrier power joint allocation algorithm. Low computational complexity and adaptive features make it available for implementation.

Adaptive Subcarrier Allocation for OFDM Relay System

This paper proposes two scheduling algorithms for subcarrier allocation of OFDM relay system, enhanced two-hop adaptive proportional fairness (E-THAPF) and user-number-dynamic two-hop adaptive proportional fairness (UND-THAPF), aiming to improve the performance of the traditional two-hop proportional fairness (THPF) scheduling algorithm. By modifying the priority of the two hops in THPF in an adaptive fashion, E-THAPF and UND- THAPF can optimize the subcarrier allocation dynamically despite of the subcarriers fluctuation, and thus can keep the system flexible and stable. Moreover, the factor α in the dynamic index of UND-THAPF is made adaptive to the change of the number of users. Simulation results show that the proposed algorithms achieve a better compromise between system fairness and spectral efficiency. In particular, while E-THAPF is designed to be adaptive to different sub-channel conditions, UND-THAPF performs even better for taking number of users into account in the optimization. 

Energy-efficient optical line terminal for WDM-OFDM-PON based on two-dimensional subcarrier and layer allocation

We propose and experimentally demonstrate a scheme to reduce the energy consumption of optical line terminal (OLT) in wavelength division multiplexing - orthogonal frequency division multiplexing - passive optical networks (WDM-OFDM-PONs). In our scheme, a wireless communication technique, termed layered modulation, is introduced to maximize the transmission capacity of OFDM modulation module in the OLT by multiplexing data from different ONU groups with signal-to-noise ratio (SNR) margins onto the same subcarriers. With adaptive and dynamic subcarrier and layer allocation, several ONU groups with low traffic demands can share one OFDM modulation module to deliver their data during non-peak hours of a day, thus greatly reducing the number of running devices and minimizing the energy consumption of the OLT. Numerical calculation shows that an energy efficiency improvement of 28.3% in the OLT can be achieved by using proposed scheme compared to the conventional WDM-OFDM-PON.

Maximum Achievement Rate Allocation Algorithm for Downlink Multi-User OFDMA Systems

In multi-user OFDMA systems, adaptive resource allocation has been identified as one of the key technologies to have more flexibility and higher efficiency. Several adaptive subcarrier allocation algorithms with the objective to maximize spectral efficiency or fairness have been proposed. However, quality of service (QoS) requirement of each user may not be supported. Some algorithms considering user’s QoS requirement have been introduced, but they do not consider the case that every user’s QoS requirement cannot be guaranteed with limited resources. In this paper, we propose a maximum achievement rate allocation (MARA) algorithm as a new adaptive resource allocation algorithm. The proposed MARA algorithm has a goal to improve overall throughput while maximizing achievement rate, i.e., maximize the number of users meeting QoS requirements. In addition, we investigate that MARA is more effective when fractional frequency reuse (FFR) is adopted as a frequency partitioning scheme. Simulation results show that the MARA algorithm improves the achievement rate as well as overall throughput. Moreover, further performance gains are achieved when FFR is adopted.

Suboptimal recursive optimisation framework for adaptive resource allocation in spectrum-sharing networks

The authors propose a suboptimal algorithm for adaptive subcarrier, bit and power allocation for orthogonal frequency division multiple access-based spectrum-sharing networks. This problem in its original form is non-convex and may be solved using greedy algorithms or integer linear programming (ILP) techniques. However, the computational complexity of the latter techniques is quite high, while the suboptimal greedy algorithms are not very well suited for spectrum-sharing networks because of multiple constraints on the transmitted power, interference leakage and individual user data rate. Therefore the authors propose a novel recursion-based linear optimisation framework that provides a solution that is very close to the optimal one and that has the ability to perform adaptive subcarrier, bit and power allocation for multiple users in the presence of multiple individual user constraints. Owing to the convexity of the proposed algorithm at each recursion, its overall complexity is substantially lower than that of the ILP-based solution.

BitQoS-Aware Resource Allocation for Multi-User Mixed-Traffic OFDM Systems

Spectral efficiency has improved significantly with the deployment of beyond third generation (3G) cellular air interfaces. However, the scarcity of unallocated radio spectrum bands, coupled with the need to provide ubiquitous wireless data services with different Quality of Service (QoS) requirements to a large number of users, has continued to drive extensive research efforts in radio resource management (RRM). In order to adapt to the changing wireless channel conditions and meet the varying and diverse QoS requirements, much of the published work in RRM has focused on exploiting multi-user and multi-channel diversities and more recently on exploiting multi-application diversity to take advantage of the mechanisms and optimization features introduced in the air interfaces. In this paper, we propose a bitQoS-aware resource allocation framework to increase the flexibility and granularity of the resource allocation algorithms by adaptively matching the QoS requirements of the user application bits to the characteristics of the Orthogonal Frequency Division Multiplexing (OFDM) subcarriers in a mixed-traffic environment. We show through an adaptive joint subcarrier, power and bit allocation algorithm, that with the finesse control of bitQoS-aware scheduling, it is possible to simultaneously achieve both an increase in user throughput and a reduction in user packet drop probability by accepting a within scheduling delay threshold increase in user latency. The performance gains obtainable are quantified in terms of system throughput, user throughput, user latency, user jitter and user packet drop probability for systems under different traffic loads.

An Optimal Adaptive Subcarrier Allocation for Multiuser MIMO-OFDM Transmission in Partial-channel Response Environment

摘要: 该文提出一种在部分信道响应环境中利用各个用户的信道反馈信息自适应调整多用户子载波分配的优化算法，该算法考虑到实际环境中反馈信息延迟和误差引起的部分信道响应情况，结合各用户的反馈信道信息和动态子载波组分配技术，可实现有效降低自适应子载波分配运算量同时又不明显弱化系统性能的目的。仿真结果表明，该算法可改善部分信道响应带来的负面影响，同时也使子载波分配算法获得较大的简化。 关键词: 多输入输出; 正交频分复用; 子载波分配; 自适应; 多用户

The Optimal Subcarrier and Bit Allocation for Multiuser OFDM System: A Dual-Decomposition Approach

The advantages of the orthogonal frequency division multiplexing (OFDM) are high spectral efficiency, resiliency to RF interference, lower multi-path distortion and others. To further utilize the vast channel capacity of the multiuser OFDM, one has to find the efficient adaptive subcarrier and bit allocation among users. In this paper, we propose a 0-1 integer programming model formulating the optimal subcarrier and bit allocation problem of the multiuser OFDM. We proved that the continuous relaxation of our formulation is tighter than the previous convex optimization formulation based on perspective function and the Lagrangian dual bound of our formulation is equivalent to the linear programming relaxation bound. The proposed Lagrangian dual is seperable with respect to subcarriers and allows an efficient dual maximization algorithm. We compared the performance of the integer programming formulation and the Lagrangian dual of our formulation and the continuous relaxation and the primal heuristic proposed in [3]. Computer simulation on a system employing M-ary quadrature amplitude modulation (MQAM) assuming a frequency-selective channel consisting of three independent Rayleigh multipaths is carried out with the optimal subcarrier and bit allocation solution generated by the 0-1 integer programming model.

복호후재전송을 사용하는 양방향 OFDMA 중계 네트워크에서 다중사용자를 위한 부반송파 할당 기법

양방향 중계 네트워크는 중계기에 중첩 부호화 또는 네트워크 부호화를 적용함으로써 기존의 단방향 중계 네트워크에 비해 향상된 주파수 효율을 제공한다. 한편, OFDMA 네트워크는 사용자에게 부반송파, 파워 등의 자원을 적응적으로 할당하여 네트워크의 성능향상을 얻을 수 있다. 본 논문에서는 복호후재전송을 사용하는 양방향 OFDMA 중계 네트워크에서 다중사용자를 위한 적응적 부반송파 할당 알고리즘을 제안한다. 제안된 알고리즘은 각 사용자 쌍의 최소 전송속도를 보장하며 모든 사용자 쌍에 대한 달성 합 전송속도를 최대화하기 위해 부반송파를 사용자 쌍과 중계기에 적응적으로 할당한다. 모의실험을 통해 제안된 알고리즘이 정적 알고리즘, 그리디 알고리즘 보다 우수한 성능을 보임을 확인한다. A two-way relay network provide improved spectral efficiency compared with a conventional one-way relay network by using either superposition coding or network coding. OFDMA network provides imptoved performance by adaptive resource allocation. In this paper, we propose a adaptive subcarrier allocation for a multiuser two-way OFDMA relay network. In the proposed algorithm, subcarriers are allocated to the user-pairs and relays to maximize the achievable sum-rate over all user-pairs while satisfying the minimum rate requirement for each user-pair. Simulation results show that the proposed algorithm provides improved performance compared with the static and greedy algorithms.

A Novel Resource Allocation Algorithm in Multi-media Heterogeneous Cognitive OFDM System

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.

Optical Orthogonal Frequency Division Multiple Access Networking for the Future Internet

To meet diverse, bandwidth-intensive applications envisioned in future optical networks, as well as address the shortcomings of the current Internet, novel networking technologies will be of great importance. We discuss several key issues for the future Internet, including network virtualization mechanisms, a programmable network architecture, parallelism of optical transmission, and guaranteed quality of service provisioning. Moreover, a new type of virtualized optical substrate architecture is proposed that utilizes optical orthogonal frequency division multiple access (OFDMA), along with subwavelength switching and generic packet routing to realize the network bandwidth programmability. The main features, benefits, and design and implementation challenges of optical OFDMA networking based on sliceable routers are also described. Finally, an adaptive subcarrier allocation and assignment algorithm for future OFDMA-based networking is investigated, and a performance comparison between the proposed approach and legacy time division multiple access (TDMA)-based techniques is drawn.