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.

This paper establishes a new unified method for fixed-length source coding problems of general sources. Specifically, we introduce an alternative definition of the smooth Renyi entropy of order zero, and show a unified approach to present the fixed-length coding rate in terms of this information quantity. Our definition of the smooth Renyi entropy has a clear operational meaning, and hence is easy to calculate for finite block lengths. Further, we represent various ε-source coding rate and the strong converse property for general sources in terms of the smooth Renyi entropy, and compare them with the results obtained by Han and Renner et al.

Low-density parity-check (LDPC) codes become very popular in channel coding, since they can achieve the performance close to maximum-likelihood (ML) decoding with linear complexity of the block length. Recently, Muramatsu et al. proposed a code using LDPC matrices for Slepian-Wolf source coding, and showed that their code can achieve any point in the achievable rate region of Slepian-Wolf source coding. However, since they employed ML decoding, their decoder needs to know the probability distribution of the source. Hence, it is an open problem whether there exists a universal code using LDPC matrices, where universal code means that the error probability of the code vanishes as the block length tends to infinity for all sources whose achievable rate region contains the rate pair of encoders. In this paper, we show the existence of a universal Slepian-Wolf source code using LDPC matrices for stationary memoryless sources.

We investigate the secret key agreement from correlated Gaussian sources in which the legitimate parties can use the public communication with limited rate. For the class of protocols with the one-way public communication, we show a closed form expression of the optimal trade-off between the rate of key generation and the rate of the public communication. Our results clarify an essential difference between the key agreement from discrete sources and that from continuous sources.

This letter treats lossy source coding of binary sources with short linear block codes. It is numerically shown that very simple basis-reprocessing approach yields good rate-distortion performance with manageable computational complexity for small block lengths. The result for code lengths up to 100 outperforms the message-passing based encoding for low-density codes which are several times longer.

In 1997, the author considered the separate coding system for two correlated memoryless Gaussian sources and squared distortion measures and determined the rate distortion region in a case where one source plays a role of the partial side information at the decoder. The above source coding system can be extended to a certain class of source network with several decoders, where each decoder has at most one full or partial side information. This class of source network is called the one-helps-one system. In this paper we consider a source network belonging to this class for correlated memoryless Gaussian sources and squared distortion measures. This source network was posed and investigated by Korner and Marton and was called the zig-zag source network. They studied the zig-zag source network in the case of discrete memoryless multiple sources. In this paper we study the zig-zag source network in the case of correlated memoryless Gaussian sources and square distortion. We determine the rate distortion region in a case where sources have a certain correlation property.

In this paper, we propose a new 3D sound rendering method for multiple sound sources with limited computational resources. The method is based on fuzzy clustering, which achieves dual benefits of two general methods based on amplitude-panning and hard clustering. In embedded systems where the number of reproducible sound sources is restricted, the general methods suffer from localization errors and/or serious quality degradation, whereas the proposed method settles the problems by executing clustering-process and amplitude-panning simultaneously. Computational cost evaluation based on DSP implementation and subjective listening test have been performed to demonstrate the applicability for embedded systems and the effectiveness of the proposed method.

Multi-source broadcasting is one of the information dissemination problems on interconnection networks such that some (but not all) units disseminate distinct information to all other units. In this paper, we discuss multi-source broadcasting on the Kautz digraph which is one of the models of interconnection networks. We decompose the Kautz digraph K(d,n) into isomorphic cycle-rooted trees whose root-cycle has length 2, then we present an algorithm for multi-source broadcasting using these cycle-rooted trees. This algorithm is able to treat d(d+1) messages simultaneously and takes the same order for required times as lower bound.

Platforms of hosting services are expected to provide a virtual private computing infrastructure with guaranteed levels of performance to support each reservation request sent by a client. To enhance the performance of the computing infrastructure in responding to reservation requests, the platforms are required to reserve, coordinate, and control globally distributed computing and network resources across multiple domains. This paper proposes Grid Network Service -- Web Services Interface version 2 (GNS-WSI2). GNS-WSI2 is a resource-reservation messaging protocol that establishes a client-server relationship. A server is a kind of management system in the management plane, and it allocates available network resources within its own domain in response to each reservation request from a client. GNS-WSI2 has the ability to reserve network resources rapidly and reliably over multiple network domains. This paper also presents the results of feasibility tests on a transpacific testbed that validate GNS-WSI2 in terms of the scalable reservation of network resources over multiple network domains. In the tests, two computing infrastructures over multiple network domains are dynamically provided for scientific computing and remote-visualization applications. The applications are successfully executed on the provided infrastructures.

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.

Estimating the number of signals (NIS) is an important goal in array signal processing, such as direction-of-arrival (DOA) estimation. A common approach for solving this problem is to use an eigenvalue of the array covariance matrix and information criterion, such as the Akaike information criterion (AIC) and minimum description length (MDL). However they suffer serious degradation, when the incoming signals are coherent. To estimate the NIS of the coherent signals impinging on a uniform linear array (ULA), a method for estimating the number of signals without eigendecomposition (MENSE) is proposed. The accuracy of the NIS estimation performance of MENSE is superior to the other algorithms equipped with preprocessing such as the spatial smoothing preprocessing (SSP) and forward/backward spatial smoothing techniques (FBSS) to decorrelate the coherency of signals. Instead of using SSP or FBSS preprocessing, MENSE uses the Hankel correlation matrices. The Hankel correlation matrices can not only decorrelate the coherency of signals but also suppress the influence of noise. However, in severe conditions like low signal-to-noise ratio (SNR) or a closely spaced signals impinging on a ULA, the NIS estimation metric of MENSE has some bias which causes estimation error. In this paper, we pay attention to the multiplicity defined by the ratio of the geometric mean to the arithmetic mean. Accordingly, we propose a new estimation metric that has less bias than that in MENSE. The Computer simulation results show that the proposed method is superior to MENSE in the above severe conditions.

In real environments, the presence of ambient noise and room reverberations seriously degrades the accuracy in sound source localization. In addition, conventional sound source localization methods cannot localize multiple sound sources accurately in real noisy environments. This paper proposes a new method of multiple sound source localization using a distributed microphone system that is a recording system with multiple microphones dispersed to a wide area. The proposed method localizes a sound source by finding the position that maximizes the accumulated correlation coefficient between multiple channel pairs. After the estimation of the first sound source, a typical pattern of the accumulated correlation for a single sound source is subtracted from the observed distribution of the accumulated correlation. Subsequently, the second sound source is searched again. To evaluate the effectiveness of the proposed method, experiments of two sound source localization were carried out in an office room. The result shows that sound source localization accuracy is about 99.7%. The proposed method could realize the multiple sound source localization robustly and stably.

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.

Multimedia multicast with two servers based on the multiterminal source coding is studied in some previous researches. Due to the possibility of providing an approach for practical code design for more than two correlated sources in IMTSC/CEO setup, in this paper, the framework of Slepian-Wolf coded quantization is extended and a practical code design is presented for IMTSC/CEO with the number of encoders greater than two. Then the multicast system based on the IMTSC/CEO is applied to the cases with three, four and five servers. Since the underlying code design approach for the IMTSC/CEO problem has the capability of applying to an arbitrary number of active encoders, the proposed MMBMSC method can also be used with an arbitrary number of servers easily. Also, explicit expressions of the expected distortion with an arbitrary number of servers in the MMBMSC system are presented. Experimental results with data, image and video signals show the superiority of our proposed method over the conventional solutions and over the MMBMSC system with two servers.

A third order harmonic oscillator has been proposed based on the resonant tunneling diode pair oscillators. This oscillator has significant advantages, good stability of the oscillation frequency against the load impedance change together with capability to output higher frequencies. Proper circuit operation has been demonstrated using circuit simulations. It has been also shown that the output frequency is stable against the load impedance change.

In this letter, we propose an interference-aware resource allocation algorithm for the uplink of OFDMA systems. It comprises a macrocell overlaid with short range femtocells. We define the interferences that occur between a macrocell and femtocells and present the resource assignment algorithm to resolve and mitigate the cross-tier interference effect based on the defined interference factors. Simulation results show that the proposed algorithm performs well in a macrocell and femtocells.

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.

The quantity and state of fishery resources must be known so that they can be sustained. The fish culture industry is also planning to investigate resources. The results of investigations are used to estimate the catch size, times fish are caught, and future stocks. We have developed a method for extracting scallop areas from gravel seabed images to assess fish resources and also developed an automatic system that measures their quantities, sizes, and states. Japanese scallop farms for fisheries are found on gravel and sand seabeds. The seabed images are used for fishery investigations, which are absolutely necessary to visually estimate, and help us avoid using the acoustic survey. However, there is no automatic technology to measure the quantities, sizes, and states of resources, and so the current investigation technique is the manual measurement by experts. There are varied problems in automating technique. The photography environments have a high degree of noise, including large differences in lighting. Gravel, sand, clay, and debris are also included in the images. In the gravel field, we can see scallop features, such as colors, striped patterns, and fan-like shapes. This paper describes the features of our image extracting method, presents the results, and evaluates its effectiveness.

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.

We propose a simplified model of real-time joint source-channel coding, which can be used to adaptively determine the quality-optimal code rate of forward error correction (FEC) coding. The objective is to obtain the maximum video quality in the receiver, while taking time-varying packet loss into consideration. To this end, we propose a simplified model of the threshold set of the residual video packet loss rate (RVPLR). The RVPLR is the rate of residual loss of video packets after channel decoding. The threshold set is defined as a set of discrete RVPLRs in which the FEC code rate must be changed in order to maintain minimum distortion during increases or decreases of channel packet loss. Because the closed form of the proposed model is very simple and has one scene-dependent model parameter, a video sender can be easily implemented with the model. To train the scene-dependent model parameters in real-time, we propose a test-run method. This method accelerates the test-run while remaining sufficiently accurate for training the scene-dependent model parameters. By using the proposed model and test-run, the video sender can always find the optimal code rate on the fly whenever there is a change in the packet loss status in the channel. An experiment shows that the proposed model and test-run can efficiently determine the near-optimal code rate in joint source-channel coding.