Data mining is a method for extracting useful information that is necessary for a system from a database. As the types of data processed by the system are diversified, the transformed pattern mining techniques for processing these type of data have been proposed. Unlike the traditional pattern mining methods, erasable pattern mining is a technique for finding the patterns that can be removed by coming with a small profit. Erasable pattern mining should be able to process data by considering both the environment that the data are generated from and the characteristics of the data. An uncertain database is a database that is composed of uncertain data. Since erasable patterns discovered from uncertain data contain significant information, these patterns need to be extracted. In addition, databases gradually increase, because the data from various fields is generated and accumulated over data streams. Data streams should be processed as intelligently as possible to provide the useful data to the system in real time. In this paper, we propose an efficient erasable pattern mining algorithm that processes uncertain data that is generated over data streams. The uncertain erasable patterns discovered through the suggested technique are more meaningful information by considering the probability of the item and the profit. Moreover, the proposed method can perform efficient mining operations by using both tree and list structures. The performance of the suggested algorithm is verified through the performance tests compared with state-of-the-art algorithms using real data sets and synthetic data sets.

A low complexity pilot allocation scheme is proposed for a large OFDM block with null subcarriers. The proposed scheme allocates pilots to the edge part of the active subcarrier region according to the 2nd order polynomial and to the middle part of the active subcarrier region according to the 1st order polynomial or the comb‐type pilot pattern. To find a parameter of the 2nd order polynomial, the proposed scheme applies exhaustive search of a single parameter by using an integer unit resolution. It is shown by simulation that the proposed scheme is a close‐to‐optimal pilot allocation scheme yielding better symbol error rate (SER) performance than the traditional 3rd and 5th order polynomial‐based schemes although the proposed scheme has lower computation and implementation complexity.

Blind selected mapping (BSLM) is a technique to reduce the peak to average power ratio (PAPR) of OFDM by using a set of scrambling sequences. Since the side information (SI) on the scrambling sequence selected by the transmitter is not directly sent to the receiver in BSLM, the SI needs to be estimated by the receiver. In this paper, a BSLM scheme that applies a new SI estimation approach is proposed. The proposed BSLM scheme estimates the SI by selecting the minimum of the candidate metrics that are computed with the received pilot signal, the pilot symbol sequence, and the scrambling sequences. It is shown by simulation that the proposed BSLM scheme yields better SI error rate (SIER) and bit error rate (BER) performance and lower implementation complexity than four traditional BSLM schemes.

A time-reversal (TR)-based transmission using pre-distortion of the transmitted waveforms for intersymbol interference (ISI) alignment is proposed. This scheme differs from the previous TR-based pre-filtering schemes in that it uses distinctively designed pre-distorted waveforms that are based on the transmitted symbol information. In the proposed pre-distortion scheme, the successively received waveforms carrying adjacent transmitted symbols are aligned so that the received symbol power can be intensified. Since the overlapped portions of the successively transmitted waveforms from the proposed pre-distortion scheme are correlated, the power of the overall transmitted signal that is formed by time-shifting and adding the pre-distorted waveforms becomes larger than the sum of the individual pre-distorted waveform powers. In order to adjust the pre-distorted waveform power without measuring the actual power of the overall transmitted signal, an upper bound on the average power of the overall transmitted signal was derived analytically under a low SNR assumption. Simulation showed that the proposed pre-distortion scheme outperformed both conventional TR and the minimum mean square error (MMSE)-based pre-filtering when the ISI was serious with a high transmission rate.

Based on the frequent pattern mining, closed frequent pattern mining and weighted frequent pattern mining have been studied to reduce the search space and discover important patterns. In the previous definition of weighted closed patterns, supports of patterns are only considered to compute the closures of the patterns. It means that the closures of weighted frequent patterns cannot be perfectly checked. Moreover, the usefulness of weighted closed frequent patterns depends on the presence of frequent patterns that have supersets with the exactly same weighted support. However, from the errors such as noise, slight changes in items' supports or weights by them have significantly negative effects on the mining results, which may prevent us from obtaining exact and valid analysis results since the errors can break the original characteristics of items and patterns. In this paper, to solve the above problems, we propose a concept of robust weighted closed frequent pattern mining, and an approximate bound is defined on the basis of the concept, which can relax requirements for precise equality among patterns' weighted supports. Thereafter, we propose a weighted approximate closed frequent pattern mining algorithm which not only considers the two approaches but also suggests fault tolerant pattern mining in the noise constraints. To efficiently mine weighted approximate closed frequent patterns, we suggest pruning and subset checking methods which reduce search space. We also report extensive performance study to demonstrate the effectiveness, efficiency, memory usage, scalability, and quality of patterns in our algorithm.

In data mining area, weight based sequential pattern mining has been suggested to find important sequential patterns by considering the weights of sequential patterns. More extensions with weight constraints have been proposed such as mining weighted

If a channel fades fast and the feedback rate of a wireless communication system is low, exploiting long-term channel statistics at the transmitter is more often practical than exploiting instantaneous channel state information. Statistical adaptive modulation scheme based on tap correlation information at the transmitter assuming an orthogonal frequency division multiplexing system with fast mobiles has been proposed. The proposed scheme improves the system performance compared with uniform bit loading scheme. It has been shown that at low SNR, statistical adaptive modulation applied to a channel with high tap correlation results in better performance than that applied to a channel without tap correlation.

In closed loop methods for obtaining exact channel state information at the transmitter (CSI-Tx), the overhead associated with the feedback can be excessive for fast mobiles. Channel-statistics-based CSI-Tx requires a much smaller overhead, and is, therefore, attractive for use with fast mobiles. We study ways to exploit correlation-based CSI-Tx in a multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. We focus on a channel environment in which spatial and tap correlation are present. We propose a channel model for the case such that spatial and tap correlation can be separated, and show that this case channel correlation decreases the ergodic capacity of a MIMO-OFDM system when no CSI-Tx is available. However, this decrease can be mitigated when correlation based CSI-Tx is exploited. We introduce an optimal precoding approach to maximize capacity with spatial- and tap-correlation-based CSI-Tx. We also propose a statistical waterfilling scheme, which leads to almost optimal capacity performance without requiring computationally intensive numerical optimization. Based on these approaches, the impact of spatial and tap correlation is investigated.

In closed-loop methods for obtaining exact channel state information at the transmitter (CSI-Tx), the overhead associated with the feedback can be excessive for fast mobiles. Channel statistics-based CSI-Tx requires a much smaller overhead and is, therefore, attractive for use with fast mobiles. We study ways to exploit correlation-based CSI-Tx in a multiple-input multiple-output (MIMO)-orthogonal frequency-division multiplexing (OFDM) system. We focus on a channel environment in which spatial and tap correlations are present. We propose a channel model for the case that spatial and tap correlations can be separated and show that in this case channel correlation decreases the ergodic capacity of an MIMO-OFDM system when no CSI-Tx is available. However, this decrease can be mitigated when correlation-based CSI-Tx is exploited. We introduce an optimal precoding approach to maximize capacity with spatial and tap correlation-based CSI-Tx. We also propose a statistical waterfilling scheme, which leads to almost optimal capacity performance without requiring computationally intensive numerical optimization. Based on these approaches, the impact of spatial and tap correlations is investigated.

The achievable average sum rate of an OFDMA uplink with multiuser adaptation based on the channel statistics information is investigated in this paper. Multiuser adaptation using channel mean and tap correlation simultaneously is shown to offer large gains in spectral efficiency compared to both uniform subcarrier and power allocation and multiuser adaptation exploiting channel mean information only. Multiuser adaptation efficiently captures multiuser diversity with limited feedback. The impacts of the Ricean K-factor, the magnitude of tap correlation and the number of simultaneously scheduled users per OFDM symbol on the average sum rate are also investigated

The impact of tap correlation on the achievable average sum rate of an OFDMA uplink is investigated. Tap correlation between channel taps was showed to reduce the average sum rate of an OFDMA uplink. However, if available subcarriers and power are allocated to multiusers based on their tap correlation information, a hefty portion of inherent multiuser diversity can be exploited in a cost effective manner leading to substantial improvement in spectral efficiency compared with uniform subcarrier and power allocation. The performance gain of such statistical adaptation is further investigated as a function of the number of simultaneously scheduled users per OFDM symbol.

We investigate ergodic capacities and optimal transmitter strategies in Rayleigh fading multiple input multiple output (MIMO) channels with spatial correlation, when there exist channel uncertainties arising from the combined effect of channel estimation error and limited feedback. We consider both covariance feedback and instantaneous feedback, and formulate optimization problems that determine the capacities and optimal transmitter designs for both cases. In the high SNR regime, the optimal solutions have simple closed form formulas that involve inverting the channel covariance and waterfilling over instantaneous channel gains. Numerical results show that instantaneous feedback gives large capacity gain at low SNR and is also helpful at high SNR. Covariance feedback, on the other hand, seems to give little gain at mid SNR, but is almost as good as instantaneous feedback at high SNR under a reasonable channel estimation quality.

We investigate the capacity behavior of an OFDM wireless link for the frequency selective MIMO channel with correlated paths. The derivation is based on a particular channel model that characterizes path correlation as well as spatial correlation. As in the case of spatial correlation, path correlation can reduce capacity. If there is no channel knowledge at the transmitter, the capacity reduction of an OFDM based system due to path correlation can be explained in terms of the effective SNR at each tone. With spatial and path correlation information at the transmitter, we derive the optimal space-frequency precoder at every tone by numerical optimization techniques. We propose a sub-optimal precoding scheme with lower complexity which leads to a tight lower bound of the capacity of the OFDM system.