In this letter, we propose a new resource allocation scheme for a two-way OFDM relay network with fairness constraints. To maximize sum capacity, subcarriers and their power are successively allocated to the relays based on channel conditions. Also, the power constraint is imposed on each relay to achieve fairness for the relays. Simulation results show that the proposed scheme improves sum capacity and fairness significantly.

A resource allocation scheme for multi-access MIMO-OFDM systems in uplink was developed to improve power and spectrum efficiency in the frequency and the space domains [1]. The scheme requires a multi-user detector in the receiver and assumes identical spatial crosscorrelation across all subcarriers for any pair of spatially separable users. However, the multi-user detection device may not exist in the receiver and the identical spatial crosscorrelation assumption may not be valid in some operational scenarios. The paper develops a scheme to remedy these problems for multi-access MIMO-OFDM systems without using multi-user detection techniques and the assumption. The proposed scheme aims at minimizing the total user transmit power while satisfying the required data rate, the maximum transmit power constraint, and the bit error rate of each user. The simulation results are presented to demonstrate the efficacy of the proposed algorithm.

In this paper, we mathematically derive a matrix-form solution named resource allocation matrix (RAM) for sub-band allocation in an orthogonal frequency division multiple access (OFDMA) system. The proposed scheme is designed to enhance throughput under a strict user fairness condition such that every user has an equal number of sub-bands per frame. The RAM designates the most preferable sub-band for every user. The proposed scheme is evaluated in terms of throughput and user fairness by comparison with the proportional fairness (PF) scheme and greedy scheme. Numerical results show that the proposed scheme has overwhelming superiority to other schemes in terms of fairness and tight competitive in terms of throughput.

Broadcasting information to users about new resource assignments generates a substantial mapping overhead. The mapping overhead influences the system throughput and, in particular, seriously affects the performance of voice-over-Internet protocol (VoIP) services. Persistent scheduling was introduced to reduce the mapping overhead. However, up to now no studies have mathematically analyzed the performance of the persistent scheduling. This paper develops analytical and simulation models and evaluates the performance of the persistent scheduling for VoIP services in mobile WiMAX systems.

Power-aware scheduling problem has been a recent issue in cluster systems not only for operational cost due to electricity cost, but also for system reliability. In this paper, we provide SLA-based scheduling algorithms for bag-of-tasks applications with deadline constraints on power-aware cluster systems. The scheduling objective is to minimize power consumption as long as the system provides the service levels of users. A bag-of-tasks application should finish all the sub-tasks before the deadline as the service level. We provide the power-aware scheduling algorithms for both time-shared and space-shared resource sharing policies. The simulation results show that the proposed algorithms reduce much power consumption compared to static voltage schemes.

The biggest challenge in multi-cell MIMO multiplexing systems is how to effectively suppress the other-cell interference (OCI) since the OCI severely decrease the system performance. Cooperation among cells is one of the most promising solutions to OCI problems. However, this solution suffers greatly from delay and overhead issues, which make it impractical. A coordinated MIMO system with a simplified cooperation between the base stations is a compromise between the theory and practice. We aim to devise an effective resource allocation algorithm based on a coordinated MIMO system that largely alleviates the OCI. In this paper, we propose a joint resource allocation algorithm incorporating intra-cell beamforming multiplexing and inter-cell interference suppression, which adaptively allocates the transmitting power and schedules users while achieving close to an optimal system throughput under proportional fairness consideration. We formulate this problem as a nonlinear combinational optimization problem, which is hard to solve. Then, we decouple the variables and transform it into a problem with convex sub-problems that can be solve but still need heavy computational complexity. In order to implement the algorithm in real-time scenarios, we reduce the computational complexity by assuming an equal power allocation utility to do user scheduling before the power allocation. Extensive simulation results show that the joint resource allocation algorithm can achieve a higher throughput and better fairness than the traditional method while maintains the proportional fairness. Moreover, the low-complexity algorithm obtains a better fairness and less computational complexity with only a slight loss in throughput.

Base station coordination is considered as a promising technique to mitigate inter-cell interference and improve the cell-edge performance in cellular orthogonal frequency division multiple-access (OFDMA) networks. The problem to design an efficient radio resource allocation scheme for coordinated cellular OFDMA networks incorporating base station coordination has been only partially investigated. In this contribution, a novel radio resource allocation algorithm with universal frequency reuse is proposed to support base station coordinated transmission. Firstly, with the assumption of global coordination between all base station sectors in the network, a coordinated subchannel assignment algorithm is proposed. Then, by dividing the entire network into a number of disjoint coordinated clusters of base station sectors, a reduced-feedback algorithm for subchannel assignment is proposed for practical use. The utility function based on the user average throughput is used to balance the efficiency and fairness of wireless resource allocation. System level simulation results demonstrate that the reduced-feedback subchannel assignment algorithm significantly improves the cell-edge average throughput and the fairness index of users in the network, with acceptable degradation of cell-average performance.

Base Station (BS) cooperation has been considered as a promising technology to mitigate co-channel interference (CCI), yielding great capacity improvement in cellular systems. In this paper, by combining frequency domain cooperation and space domain cooperation together, we design a new CCI mitigation scheme to maximize the total utility for a multi-cell OFDMA network. The scheme formulates the CCI mitigation problem as a mixture integer programming problem, which involves a joint user-set-oriented subcarrier assignment and power allocation. A computationally feasible algorithm based on Lagrange dual decomposition is derived to evaluate the optimal value of the problem. Moreover, a low-complexity suboptimal algorithm is also presented. Simulation results show that our scheme outperforms the counterparts incorporating BS cooperation in a single domain considerably, and the proposed low-complexity algorithm achieves near optimal performance.

In a conventional downlink OFDMA system, an underlay secondary network is co-located to formulate a new implementation of OFDMA-based cognitive radio (OCR), where spectrum sharing is enabled between primary users and secondary users. With the introduced concept of accessible interference temperature, this new model can be easily implemented and may contribute to the future realization of OCR systems.

This paper proposes an adaptive resource allocation for multi-tier computing systems to guarantee a fair QoS level under resource constraints of tiers. We introduce a multi-tier computing architecture which consists of a group of resource managers and an arbiter. Resource allocation of each client is managed by a dedicated resource manager. Each resource manager updates resources allocated to subtasks of its client by locally exchanging QoS levels with other resource managers. An arbiter compensates the updated resources to avoid overload conditions in tiers. Based on the compensation by the arbiter, the subtasks of each client are executed in corresponding tiers. We derive sufficient conditions for the proposed resource allocation to achieve a fair QoS level avoiding overload conditions in all tiers with some assumptions on a QoS function and a resource consumption function of each client. We conduct a simulation to demonstrate that the proposed resource allocation can adaptively achieve a fair QoS level without causing any overload condition.

This paper proposes two novel frame resource allocation schemes: Mixed bidirectional allocation scheme and Offset allocation scheme. They improve system capacity and latency performance unlike the conventional time-division duplex relay scheme which divides the frame structure into time segments for the access zone and time segment for the relay zones as in IEEE802.16j (WiMAX) systems. Computer simulations confirm that the two proposed schemes outperform the conventional schemes in terms of throughput and latency. An evaluation of the offset allocation scheme confirms that it improves the total throughput by about 85%, and reduces latency by about 72%, compared to the conventional schemes.

Multi-cell resource allocation under minimum rate request for each user in OFDMA networks is addressed in this paper. Based on Lagrange dual decomposition theory, the joint multi-cell resource allocation problem is decomposed and modeled as a limited-cooperative game, and a distributed multi-cell resource allocation algorithm is thus proposed. Analysis and simulation results show that, compared with non-cooperative iterative water-filling algorithm, the proposed algorithm can remarkably reduce the ICI level and improve overall system performances.

Hierarchical constellations offer a different property of robustness to the multiple bits that construct a symbol according to channel errors. We apply the characteristics of hierarchical constellations to a multi-user cellular system that has limited modulation levels, in order to improve cell capacity. We propose an adaptive resource allocation scheme based on the hierarchical constellation in which a symbol is shared by multiple users and each bit in a symbol is allocated adaptively according to the channel condition of each user. The numerical results show that the proposed resource allocation scheme provides mobile users with higher modulation levels so that the cell capacity is improved.

Traditional double auction protocols only concern the price information of participants without considering their QoS requirements, which makes them unsuitable for the service grid. In this paper we first introduce QoS information into double auction to present the QoS-enabled Double Auction Protocol (QDAP). QDAP tries to assign the asks which have the least candidate bids firstly to make more participants trade and provides QoS guarantee at the same time. Simulation experiments have been performed to compare QDAP with two traditional double auction protocols and the result shows that QDAP is more suitable for the service grid.

In this paper, we propose a new subcarrier allocation algorithm for a downlink OFDMA relay network with multicells. In the proposed algorithm, subcarriers are allocated to users and relays to maximize the overall sum of the achievable rate under fairness constraints. Simulation results show that the proposed algorithm achieves higher data rate than the static algorithm and reduces the outage probability compared to the static and greedy algorithms.

In most cases in wireless networks, a user has a two-way communication that consists of two sessions: uplink and downlink sessions, and its overall satisfaction to the communication depends on the quality of service of both sessions. However, in most previous approaches in wireless resource allocation, the satisfactions of a user for its uplink and downlink sessions are modeled separately and treated independently, which fails to accurately model user's overall satisfaction to its communication. Hence, in this paper we model user's overall satisfaction to its communication considering both its uplink and downlink sessions. To this end, we propose a novel concept for a utility function to model user's overall satisfaction to its communication, which is called a user-level utility function, considering user's satisfaction to uplink and downlink sessions jointly. To show the appropriateness of our approach, we apply our user-level utility functions to scheduling problems in TDMA wireless networks and show the performance improvement of our approach over the traditional approach that does not treat uplink and downlink sessions of a user jointly.

In this letter we propose a novel resource allocation and admission control strategy for OFDMA-based emerging LTE systems. Considering users' reneging and migration between service providers, we first prove that the optimal resource allocation problem, which maximizes the service provider's gross income is, NP-complete. Subsequently, we propose two different heuristics based on dynamic programming and greedy algorithms to get a near-optimal resource allocation and admission control strategy in computationally feasible time. Simulation results point out that the solutions offer increased gross income of the service provider, while offering low latency, adequate throughput and session acceptance.

Traditional algorithms for dynamic OFDMA resource allocation have relatively deterministic system capacity and user fairness. Thus, in this letter, an efficient scheme is proposed to flexibly adjust quality-of-service for users, which is achieved by appropriately setting minimum data-rate of each user.

In deep-submicron technology, several state-of-the-art architectural synthesis flows have already adopted the distributed register architecture to cope with the increasing wire delay by allowing multicycle communication. In this article, we regard communication synthesis targeting a refined regular distributed register architecture, named RDR-GRS, as a problem of simultaneous data transfer routing and scheduling for global interconnect resource minimization. We also present an innovative algorithm with regard of both spatial and temporal perspectives. It features both a concentration-oriented path router gathering wire-sharable data transfers and a channel-based time scheduler resolving contentions for wires in a channel, which are in spatial and temporal domain, respectively. The experimental results show that the proposed algorithm can significantly outperform existing related works.

In this paper, we propose a scheme of frequency sub-band allocation to obtain maximum throughput in an orthogonal frequency division multiple access (OFDMA) system where each user has a finite number of packets to transmit, which are generated from packet calls with arbitrary size and arbitrary arrival rate. The proposed scheme is evaluated in terms of throughput and user fairness in comparison with the proportional fairness (PF) scheme and the Greedy scheme under the finite queue length condition. Numerical results show that the proposed scheme is superior to the Greedy scheme in terms of both throughput and fairness for finite queue length.