In multiple antenna systems that use spatial multiplexing to raise transmission rates, it is preferable to use maximum likelihood (ML) detection to exploit the full receive diversity and minimize the error probability. In this paper, we present two tree based approximate ML detectors that use new two ordering criteria in conjunction with efficient search strategies. Unlike conventional tree detectors, the new detectors closely approximate the error performance of the exact ML detector while achieving a dramatic reduction in complexity. Moreover, they ensure a fixed detection delay and high level of parallelization in the tree search.

The downlink beamforming weights which can suppress interfering signals toward out-of-cell mobile stations for a TDD-based OFDMA system are introduced. First, the downlink beamforming weights are optimally designed based on iteration. Then, the downlink beamforming weights are designed in a sub-optimal way. It is shown that the sub-optimally designed downlink beamforming weights have the same structure as that of the uplink beamforming weights which are derived based on MMSE. The performance of these schemes is compared based on the average receive SINR. The performance of a heuristic scheme which exploits uplink beamforming weights for downlink beamforming weights is also investigated.

In this paper, the multi-user multiple-input multiple-output (MU-MIMO) relay channel is investigated, where the source node provides multi-beams to multi-users via a multi-antenna relay node. In this scenario, linear processing matrix at the relay node is designed around block diagonal (BD) scheme to improve the system sum-rate. Compared with the traditional linear processing matrix with zero-forcing (ZF) scheme at the relay node, the proposed matrix based on BD scheme can not only eliminate the multi-user interference to the same extent as the ZF scheme, but also realize optimal power allocation at the relay node. Numerical simulations demonstrate the BD scheme outperforms the ZF scheme and can significantly improve the sum-rate performance.

When a store sells items to customers, the store wishes to determine the prices of the items to maximize its profit. Intuitively, if the store sells the items with low (resp. high) prices, the customers buy more (resp. less) items, which provides less profit to the store. So it would be hard for the store to decide the prices of items. Assume that the store has a set V of n items and there is a set E of m customers who wish to buy those items, and also assume that each item i ∈ V has the production cost di and each customer ej ∈ E has the valuation vj on the bundle ej ⊆ V of items. When the store sells an item i ∈ V at the price ri, the profit for the item i is pi=ri-di. The goal of the store is to decide the price of each item to maximize its total profit. We refer to this maximization problem as the item pricing problem. In most of the previous works, the item pricing problem was considered under the assumption that pi ≥ 0 for each i ∈ V, however, Balcan, et al. [In Proc. of WINE, LNCS 4858, 2007] introduced the notion of "loss-leader," and showed that the seller can get more total profit in the case that pi < 0 is allowed than in the case that pi < 0 is not allowed. In this paper, we derive approximation preserving reductions among several item pricing problems and show that all of them have algorithms with good approximation ratio.

Fuzzy inference has played a significant role in many applications. Although the simplified fuzzy inference method is currently mostly used, the problem is that the number of fuzzy rules becomes very huge and so the setup and adjustment of fuzzy rules become difficult. On the other hand, Yubazaki et al. have proposed a "single input rule modules connected fuzzy inference method" (SIRMs method) whose final output is obtained by summarizing the product of the importance degrees and the inference results from single input fuzzy rule module. Seki et al. have shown that the simplified fuzzy inference method and the SIRMs method are equivalent when the sum of diagonal elements in rules of the simplified fuzzy inference method is equal to that of cross diagonal elements. This paper clarifies the conditions for the infimum and supremum of the fuzzy inference method using the single input type fuzzy inference method, from the view point of fuzzy inference.

An energy-efficient clustering scheme to maximize the network lifetime is presented in IEEE 802.15.4 networks. In the proposed clustering scheme, even though the cluster is divided into several sub-clusters in order to decrease data redundancies, the sub-CH does not transmit the beacon frame due to the problem of beacon collision. Our clustering scheme also allows the CH to control the size of the sub-cluster according to the residual energy of the sub-CH. The performance of the proposed scheme is verified by simulations that demonstrate how our scheme provides a better network lifetime than the conventional scheme.

A new LiTaO3 electro-optic polarization modulator utilizing traveling-wave electrodes and a double periodic poling structure is proposed. Utilizing the double periodic poling structure, both quasi-phase matching between TE and TM guided-modes, and quasi-velocity matching between a lightwave and a modulation microwave are obtainable at modulation frequencies over 10 GHz.

In this letter, we propose a hybrid authentication algorithm to alleviate the latent security problems of mobile multi-hop networks. The proposed scheme uses centralized authentication when a node first joins the network, and uses distributed authentication for the hop-by-hop authentication among multi-hop nodes. We also analyze performance of the proposed scheme.

In this paper, a Kalman filter-based method for restoration of video images acquired by an in-vehicle camera in foggy conditions is proposed. In order to realize Kalman filter-based restoration, the proposed method clips local blocks from the target frame by using a sliding window and regards the intensities in each block as elements of the state variable of the Kalman filter. Furthermore, the proposed method designs the following two models for restoration of foggy images. The first one is an observation model, which represents a fog deterioration model. The proposed method automatically determines all parameters of the fog deterioration model from only the foggy images to design the observation model. The second one is a non-linear state transition model, which represents the target frame in the original video image from its previous frame based on motion vectors. By utilizing the observation and state transition models, the correlation between successive frames can be effectively utilized for restoration, and accurate restoration of images obtained in foggy conditions can be achieved. Experimental results show that the proposed method has better performance than that of the traditional method based on the fog deterioration model.

This paper proposes a method providing efficient test compression. The proposed method is for robust testable path delay fault testing with scan design facilitating two-pattern testing. In the proposed method, test data are interleaved before test compression using statistical coding. This paper also presents test architecture for two-pattern testing using the proposed method. The proposed method is experimentally evaluated from several viewpoints such as compression rates, test application time and area overhead. For robust testable path delay fault testing on 11 out of 20 ISCAS89 benchmark circuits, the proposed method provides better compression rates than the existing methods such as Huffman coding, run-length coding, Golomb coding, frequency-directed run-length (FDR) coding and variable-length input Huffman coding (VIHC).

With the rapid progress of electronic and information technology, an expectation for the realization of body area network (BAN) by means of ultra wide band (UWB) techniques has risen. Although the signal from a single UWB device is very low, the energy absorption may increase significantly when many UWB devices are simultaneously adorned to a human body. An analysis method is therefore required from the point of view of biological safety evaluation. In this study, two approaches, one is in the time domain and the other is in the frequency domain, are proposed for the specific energy absorption (SA) and the specific absorption rate (SAR) calculation. It is shown that the two approaches have the same accuracy but the time-domain approach is more straightforward in the numerical analysis. By using the time-domain approach, SA and SAR calculation results are given for multiple UWB pulse exposure to an anatomical human body model under the Federal Communications Commission (FCC) UWB limit.

Jitter is the variation of latencies, when real-time Intellectual Properties (IPs) are accessing data from the data storages. It is a critical factor for such IPs from the Quality-of-Service (QoS) perspective. Jitter of a real-time IP can be measured by how frequently it experiences the underflows and overflows from its data queue in read mode and write mode, respectively. Such failures critically depend on the bus arbitration scheme which determines the bus acquisition order of IPs. The proposed idea allows IPs to inform the bus arbiter of the status of their data buffers when they assert bus requests. Such information helps the bus arbiter to determine the bus acquisition order while greatly reducing the jitter. The experimental results show that our method effectively eliminates the overflows and underflows of real-time IPs by dynamically preempting the jitter-critical bus requests.

We have proposed a tunable laser with silica-waveguide ring resonators. In this tunable laser, a semiconductor optical amplifier was passively aligned and mounted onto a silica-waveguide substrate. The ring resonators can be tuned by controlling their temperatures using the thermo optic heaters formed on them, and there are no mechanically moving parts. Thus, they are sufficiently stable and reliable for practical use. Our tunable laser exhibits a high fiber-output power of more than 15 dBm and a wide tunable range of 60 nm (L-band, 50 GHz spacing, 147 channels). Moreover, a tunable laser with a much wider tunable range of 96 nm using 100-GHz-FSR ring resonators is also reported.

A self-stabilizing protocol is a protocol that achieves its intended behavior regardless of the initial configuration (i.e., global state). Thus, a self-stabilizing protocol is adaptive to any number and any type of topology changes of networks: after the last topology change occurs, the protocol starts to converge to its intended behavior. This advantage makes self-stabilizing protocols extremely attractive for designing highly dependable distributed systems on dynamic networks. While conventional self-stabilizing protocols require that the networks remain static during convergence to the intended behaviors, some recent works undertook the challenge of realizing self-stabilization in dynamic networks with frequent topology changes. This paper introduces some of the challenges as a new direction of research in self-stabilization.

This paper focuses on optical integration technology and its application in optical microsensors used in biomedical fields. The integration is based on the hybrid integration approach, achieving high performance, small size and weight, and lower cost. First, we describe the key technologies used in hybrid integration, namely passive alignment technology, low temperature bonding technology, and packaging technology for realizing advanced microsensors. Then, we describe an integrated laser Doppler flowmeter that can monitor blood flow in human skin.

The average age of population is predicted to be raised universally but the number of nursing staff is not increasing at the same rate. This leads us to the situation where, e.g., we have too many patients for one nurse. On the other hand, sparse population in some regions, such as Northern or Eastern Finland, causes a severe problem that doctors are far away from patient. In this paper, we summarize the possibilities and applications that utilize wireless technologies in healthcare sector and which can be useful in nursing activities. The use of new innovations is one way to solve the problems that are based on the expected lack of professional staff in the future. Despite of the very natural hospital link, the developed technical solutions have applications outside hospital. Remote care of aging people and other special groups need to be done daily and almost real-time. Keeping people home instead of hospital is one way to decrease the entire care costs. In addition to the obvious human context, we derive some other applications where we can benefit wireless nursing and remote sensing techniques.

We present a 10-bit 1-MS/s successive approximation analog-to-digital converter core including a charge redistribution digital-to-analog converter and a comparator. A new linearity calibration technique enables use of a nearly minimum capacitor limited by kT/C noise. The ADC core without digital control blocks has been fabricated in a 0.18-µm CMOS process and consumes 118 µW at 1.8 V power supply. Also, the active area of ADC core is realized to be 0.027 mm2. The calibration improves the SNDR by 13.4 dB and the SFDR by 21.0 dB. The measured SNDR and SFDR at 1 kHz input are 55.2 dB and 73.2 dB respectively.

Multiple Input Multiple Output (MIMO) represents a highly promising technique for 4G communication networks as it uses multiple antennas at the transmitter and receiver to improve the reliability of transmissions and to provide a high data rate. This paper introduces an adjustable scheduling algorithm for multi-user MIMO systems that can provide an advantageous trade-off solution between throughput maximization and fair resource allocation among users. Specifically, our algorithm is proposed as a solution to system requirement issues through the flexible control of fairness factors.

An adaptive zero forcing maximum likelihood soft input soft output (AZFML-SISO) detector for multiple input multiple output (MIMO) wireless systems is presented. Its performance in an iterative MIMO receiver is analyzed. The AZFML-SISO detector calculates the soft outputs, applying the ML approach to the list that contains only those signal vectors limited by a hypersphere around the zero forcing (ZF) solution. The performance of the algorithm is evaluated on a communication system based on the standard for single carrier broadband wireless communication IEEE 802.16, with three transmit and three receive antennas. It is shown by computer simulation that the computational complexity in an average sense of the receiver running the AZFML-SISO algorithm is reduced by 90% at the SNR values of 30 dB and by 50% for SNR values of 15 dB in comparison to the receiver with an ML detector, while the system performance degrades by less than 1 dB.

The purpose of this study is the real-time estimation of Doppler spectral moments for precipitation in the presence of ground clutter overlap. The proposed method is a frequency domain approach that uses a Gaussian model both to remove clutter spectrum and to estimate weather spectrum. The main advantage of this method is that it does not use processes like several fitting procedures and enables to estimate profiles of precipitation in a short processing time. Therefore this method is efficient for real-time radar observation with high range and time resolution. The performance of this method is evaluated based on simulation data and the observation data acquired by the Ku-band broad band radar (BBR) [1].