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 (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.

We have investigated the bottleneck in web-based MORPG system and proposed a load-distribution method using multiple web servers. This technique uses a dynamic data allocation method, called the moving home. This paper describes the evaluation of our method using 4, 8, 16 web servers. We evaluated it on both the single-server system and multi-server system. And we confirm that the effect of the moving home through the comparison between the multi-server system without the moving home and that with the moving home. Our experimental result shows that the upper bound of the number of avatars in the eight-server system with the moving home becomes 380 by contrast that in the single-server system is 200.

This letter examines the problem of allocating the subcarrier power of the relayed signal in orthogonal frequency division multiplexing (OFDM) based dual-hop systems in which the relay terminal is operated in an Amplify-and-Forward (AF) mode and the source node transmits its signal with a uniform power distribution. In AF relaying systems, both the modulation order and the error control scheme are fixed at the relay node, and thus the potential for increasing the data rate via a suitable allocation of the subcarrier power at the relay node does not exist. Therefore, this study proposes an alternative subcarrier power allocation scheme in which the objective is to scale the power assigned to each of the relayed signal sub-carriers in such a way as to minimize the equivalent average noise power at the destination terminal.

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.

In this letter, we address the problem of downlink power allocation for the generalized distributed antenna system (DAS) with cooperative clusters. Considering practical applications, we assume that only the large-scale channel state information is available at the transmitter. The power allocation scheme is investigated with the target of ergodic achievable sum rate maximization. Based on some approximations and the Rayleigh Quotient Theory, the simple selective power allocation scheme is derived for the low SNR scenario and the high SNR scenario, respectively. The methods are applicable in practice due to their low complexity.

This letter proposes an intra-cell partial spectrum reuse (PSR) scheme for cellular OFDM-relay networks. The proposed method aims to increase the system throughput, while the SINR of the cell edge users can be also promoted by utilizing the PSR scheme. The novel pre-allocation factor γ not only indicates the flexibility of PSR, but also decreases the complexity of the reuse mechanism. Through simulations, the proposed scheme is shown to offer superior performances in terms of system throughput and SINR of last 5% users.

This paper presents an adaptive modulation and power allocation method for uplink multiuser multiple-input multiple-output systems under the assumption that there is perfect channel information at the receiver but not at the transmitter. The receiver jointly optimizes the power level and modulation order for all users under constraints of transmit power and error requirements, and returns these information to each user via a low-rate feedback channel. Power and modulation optimization maximizes the total throughput under a tolerable bit error ratio for each user. The ellipsoid method is used to design efficient algorithms for optimal power and modulation level.

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.

A fine-grain bit-serial multiple-valued reconfigurable VLSI based on logic-in-control architecture is proposed for effective use of the hardware resources. In logic-in-control architecture, the control circuits can be merged with the arithmetic/logic circuits, where the control and arithmetic/logic circuits are constructed by using one or multiple logic blocks. To implement the control circuit, only one state in a state transition diagram is allocated to one logic block, which leads to reduction of the complexity of interconnections between logic blocks. The fine-grain logic block is implemented based on multiple-valued current-mode circuit technology. In the fine-grain logic block, an arbitrary 3-variable binary function can be programmed by using one multiplexer and two universal literal circuits. Three-variable binary functions are used to implement the control circuit. Moreover, the hardware resources can be utilized to construct a bit-serial adder, because full-adder sum and carry can be realized by programming in the universal literal circuit. Therefore, the logic block can be effectively reconfigured for arithmetic/logic and control circuits. It is made clear that the hardware complexity of the control circuit in the proposed reconfigurable VLSI can be reduced in comparison with that of the control circuit based on a typically sequential circuit in the conventional FPGA and the fine-grain field-programmable VLSI reported until now.

ICI (Inter-Cell Interference) mitigation schemes at the cell border are frequently dealt with as a special issue in 3GPP LTE (Long Term Evolution). However, few papers have analyzed the outage performance for the ICI mitigation schemes. In this paper, we propose a generalized cell planning scheme termed QBPA (Quality of Service based Band Power Allocation). Utilizing the QBPA scheme, we measure how much increase in channel capacity can be obtained through the flexible control of bandwidth and power in multi-cell forward-link environments. In addition, the feasible performance of the conventional schemes can be evaluated as long as those schemes are specific forms of the QBPA.

H.264/AVC encoder employs rate control to adaptively adjust quantization parameter (QP) to enable coded video to be transmitted over a constant bit-rate (CBR) channel. In this topic, bit allocation is crucial since it is directly related with actual bit generation and the coding quality. Meanwhile, the rate-distortion-optimization (RDO) based mode-decision technique also affects performance a lot for the strong relation among mode, bits, and quality. This paper presents a multi-stage rate control scheme for R-D optimized H.264/AVC encoders under CBR video transmission. To enhance the precision of the complexity estimation and bit allocation, a frequency-domain parameter named mean-absolute-transform-difference (MATD) is adopted to represent frame and macroblock (MB) residual complexity. Second, the MATD ratio is utilized to enhance the accuracy of frame layer bit prediction. Then, by considering the bit usage status of whole sequence, a measurement combining forward and backward bit analysis is proposed to adjust the Lagrange multiplier λMODE on frame layer to optimize the mode decision for all MBs within the current frame. On the next stage, bits are allocated on MB layer by proposed remaining complexity analysis. Computed QP is further adjusted according to predicted MB texture bits. Simulation results show the PSNR improvement is up to 1.13 dB by using our algorithm, and the stress of output buffer control is also largely released compared with the recommended rate control in H.264/AVC reference software JM13.2.

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.

Previously, we have proposed an access point (AP) allocation algorithm in indoor environments for the Wireless Internet-access Mesh NETwork (WIMNET) using one gateway (GW) to the Internet. WIMNET consists of multiple APs that are connected wirelessly mainly by the Wireless Distribution System (WDS), to expand the coverage area inexpensively and flexibly. In this paper, we present two extensions of this algorithm to enhance the applicability to the large-scale WIMNET. One is the multiple GW extension of the algorithm to increase the communication bandwidth with multiple GWs, where all the rooms in the network field are first partitioned into a set of disjoint GW clusters and then, our previous allocation algorithm is applied to each GW cluster sequentially. The APs in a GW cluster share the same GW. The other is the dependability extension to assure the network function by maintaining the connectivity and the host coverage, even if one link/AP fault occurs, where redundant APs are added to the AP allocation by our previous algorithm. The effectiveness of our proposal in terms of the number of APs and the throughput is verified through simulations using the WIMNET simulator.

Based on game theory, a distributed power control algorithm with sequential subchannel nulling is proposed for ad-hoc networks. It is shown that the proposed method, by sharing subchannels appropriately according to the interference profiles, can reduce the power consumption of the network while satisfying the target rate of each link.

The dynamic channel allocation (DCA) scheme in multi-cell systems causes serious inter-cell interference (ICI) problem to some existing calls when channels for new calls are allocated. Such a problem can be addressed by advanced centralized DCA design that is able to minimize ICI. Thus, in this paper, a centralized DCA is developed for the downlink of multi-cell orthogonal frequency division multiple access (OFDMA) systems with full spectral reuse. However, in practice, as the search space of channel assignment for centralized DCA scheme in multi-cell systems grows exponentially with the increase of the number of required calls, channels, and cells, it becomes an NP-hard problem and is currently too complicated to find an optimum channel allocation. In this paper, we propose an ant colony optimization (ACO) based DCA scheme using a low-complexity ACO algorithm which is a kind of heuristic algorithm in order to solve the aforementioned problem. Simulation results demonstrate significant performance improvements compared to the existing schemes in terms of the grade of service (GoS) performance and the forced termination probability of existing calls without degrading the system performance of the average throughput.

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.

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.

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.