Capacity statistics and scheduling gain for MIMO systems in correlated Rayleigh fading
Taking into account realistic propagation environments, in the presence of spatial fading correlation at both the transmitter and the receiver, we derive closed-form analytical expressions for the exact characteristic function and statistical moments (mean, variance, skewness, and kurtosis) of instantaneous capacity for multiple-input multiple-output (MIMO) wireless channels. These results enable us to analytically evaluate two relevant information-theoretic capacity measures - ergodic and outage capacity - and other higher-order statistics of the capacity. We also analyze the multi-user scheduling gain in rate-feedback systems using the Gaussian approximation to the capacity distribution.

title: Capacity of multiple-antenna fading channels: spatial fading correlation, double scattering, and keyhole
abstract: The capacity of multiple-input multiple-output (MIMO) wireless channels is limited by both the spatial fading correlation and rank deficiency of the channel. While spatial fading correlation reduces the diversity gains, rank deficiency due to double scattering or keyhole effects decreases the spatial multiplexing gains of multiple-antenna channels. In this paper, taking into account realistic propagation environments in the presence of spatial fading correlation, double scattering, and keyhole effects, we analyze the ergodic (or mean) MIMO capacity for an arbitrary finite number of transmit and receive antennas. We assume that the channel is unknown at the transmitter and perfectly known at the receiver so that equal power is allocated to each of the transmit antennas. Using some statistical properties of complex random matrices such as Gaussian matrices, Wishart (1928) matrices, and quadratic forms in the Gaussian matrix, we present a closed-form expression for the ergodic capacity of independent Rayleigh-fading MIMO channels and a tight upper bound for spatially correlated/double scattering MIMO channels. We also derive a closed-form capacity formula for keyhole MIMO channels. This analytic formula explicitly shows that the use of multiple antennas in keyhole channels only offers the diversity advantage, but provides no spatial multiplexing gains. Numerical results demonstrate the accuracy of our analytical expressions and the tightness of upper bounds.

title: New Disk Scheduling Algorithms for Reduced Rotational Latency
abstract: Disk arm scheduling algorithms have been studied for many years to increase disk I/O performance. Most of the disks by the early 1980’s are characterized as a linear seek time and their seek time is responsible for the most time of disk access. So, the existing disk scheduling algorithms have focused on the reduction of the average seek distance. Seek time has improved greatly and today’s disks usually have nonlinear seek time characteristics, whereas the rotation speed has been steady at the 3600 RPM. So, it is of value to reduce average rotational latency. In this paper we propose two disk scheduling algorithms, i.e. Shortest Rotational Latency First(SRLF) and Shortest Access Tie Fist(SATF) for reduced rotational latency. SRLF services first a request with the shortest expected rotational latency and SATF services first a request with the shortest expected access time. We analyze the expected access time of the request serviced first by each of SSTF and SRLF under the uniform cylinder access. We evaluated the response time of SSTF, SRLF, and SATF through the simulations under the uniform and localized cylinder access. The results of the analysis and simulations show that the algorithms proposed in this paper are more efficient than SSTF which is known for the fastest response time.

title: Invariance of neighborhood relation under input space to feature space mapping
abstract: If the training pattern set is large, it takes a large memory and a long time to train support vector machine (SVM). Recently, we proposed neighborhood property based pattern selection algorithm (NPPS) which selects only the patterns that are likely to be near the decision boundary ahead of SVM training Proc. of the 7th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Lecture Notes in Artificial Intelligence (LNAI 2637), Seoul, Korea, pp. 376-387. NPPS tries to identify those patterns that are likely to become support vectors in feature space. Preliminary reports show its effectiveness: SVM training time was reduced by two orders of magnitude with almost no loss in accuracy for various datasets. It has to be noted, however, that decision boundary of SVM and support vectors are all defined in feature space while NPPS described above operates in input space. If neighborhood relation in input space is not preserved in feature space, NPPS may not always be effective. In this paper, we show that the neighborhood relation is invariant under input to feature space mapping. The result assures that the patterns selected by NPPS in input space are likely to be located near decision boundary in feature space.

title: Automated ordering of fingerprinted clones
abstract: A considerable amount of human intervention is currently required to produce high-quality fingerprint-based physical maps for genomic studies.



An algorithm has been developed and implemented to automatically order fingerprinted clones within contigs. The resulting software, named CORAL (Clone ORdering ALgorithm), has been tested on maps that have previously been manually edited and on maps derived from in silico simulations. The fingerprint map and DNA sequence of the human genome has provided an additional test to CORAL. Measurements suggest that CORAL performs significantly better than the software currently used by most laboratories to order fingerprinted clones at throughputs far exceeding those that can be achieved manually.

title: The study of quick download mechanism in an infrastructural wireless environment
abstract: Frequent handoff consumes a lot of system capability and signalling resources in a mobile system. In this paper, we present download mechanisms in mobile systems or broadcast systems to support data users to receive the whole packet in time before moving out of the coverage area. Three download strategies: Quick Download using Multi-channel (QDM) scheme, Prior Download using Single channel (PDS) scheme and the Quit Download (QUD) scheme are proposed in this study where the efficiencies of the three strategies are compared with the one without particular treatment. Some significant estimations such as the percentage of handoff data users having completed service before leaving the cell, the mean waiting time of non-handoff data users, and the blocking probability of data users are analysed and compared. The numerical results show that, the QDM strategy is most efficient in reducing the handoff rate, the QUD strategy can assure the waiting time of non-handoff data users and the PDS strategy can keep the handoff rate constant at light and heavy voice load. Furthermore, various number of guard channels for data users are evaluated in terms of data and voice performance based on various download strategies.

title: Response modeling with support vector machines
abstract: Support Vector Machine (SVM) employs Structural Risk Minimization (SRM) principle to generalize better than conventional machine learning methods employing the traditional Empirical Risk Minimization (ERM) principle. When applying SVM to response modeling in direct marketing, however, one has to deal with the practical difficulties: large training data, class imbalance and scoring from binary SVM output. For the first difficulty, we propose a way to alleviate or solve it through a novel informative sampling. For the latter two difficulties, we provide guidelines within SVM framework so that one can readily use the paper as a quick reference for SVM response modeling: use of different costs for different classes and use of distance to decision boundary, respectively. This paper also provides various evaluation measures for response models in terms of accuracies, lift chart analysis, and computational efficiency.