Yoo-jin Choi

On Effectiveness of Application-Layer Coding

The effectiveness of application-layer coding in a system with a large number of users is considered. The end users encode data packets before transmitting them. The effect of additional packets on the system performance is twofold: (i) additional packets increase offered load, which results in higher drop probability, and (ii) some of dropped packets can be recovered at the receivers after decoding. It is argued that the space of all systems can be partitioned into two regions where coding is beneficial and detrimental, respectively. In particular, the paper establishes an asymptotic regime that contains the boundary between these two regions. On the boundary, systems with and without coding have the same performance. Informally, our results indicate that application-layer coding improves the performance only in systems with low loss probabilities (without coding), and employing such coding in systems with high loss probabilities only degrades the performance.

Low-Complexity 2D LMMSE Channel Estimation for OFDM Systems

In this paper, we propose a novel method of reducing the complexity of a pilot-based two-dimensional linear minimum mean square error (2D LMMSE) channel estimation scheme for orthogonal frequency division multiplexing (OFDM) systems. We identify that the 2D LMMSE channel estimation method aided by pilots embedded in a two-dimensional OFDM resource grid can be decoupled into three steps: (a) pilot denoising, (b) interpolation in each of OFDM symbols including pilots, and (c) interpolation across OFDM symbols. In the denoising step, we process pilots only for noise reduction. In the following interpolation steps, we utilize two-dimensional channel correlation across subcarriers (frequency) and across OFDM symbols (time) in order to get channel estimates of interest. Under the assumption that the frequency and time correlations are disjoint and the channel correlation can be represented by the product of them, we show that the channel interpolation can be performed in two steps along the frequency domain first and then along the time domain. By taking advantage of this separation, we can reduce the complexity of 2D LMMSE considerably while still achieving the optimal performance of it.

On the departure process of the linear loss network

This paper considers a

On a critical regime for linear finite-buffer networks

k

Iterative Interference Modulation Classification

k-node linear loss network consisting of bufferless nodes. In particular, the asymptotic behavior of the departure process is investigated, as the size of the network grows. Our result provides a complete characterization of a properly scaled limiting departure process, i.e., the joint probability density function of any finite number of consecutive inter-departure times, as the size of the network increases.

Display apparatus and control method thereof

This paper considers the problem of mismatched hypothesis testing, where approximate likelihood functions are used instead of true likelihood functions. Given a hypothesis testing problem, the maximum likelihood (ML) solution is known to be optimal when true likelihood functions are used, but the optimality does not hold anymore if mismatched approximate likelihood functions are employed instead, in order to reduce computational complexity, for instance. In this paper, we investigate the mismatched ML framework using approximate likelihood functions, while the mismatches between the true and the approximate likelihood functions are corrected by additive compensating constants. The probability of error of this mismatched hypothesis testing is analyzed asymptotically, assuming a large number of samples, and the compensating constants that maximize the error exponent are established. The general results on the mismatched hypothesis testing are then utilized in designing and optimizing a digital modulation classifier with low complexity.

TV display screen displaying GUI

Linear networks consisting of finite-buffer nodes in tandem are considered. In particular, throughput properties of such networks are investigated, as their size increases. Using an approximation, we establish an asymptotic critical loading regime in which the ratio of the throughput to the input arrival rate is strictly within (0, 1). Such a regime is desirable from the point of view of both the throughput and network cost. Our results indicate that the qualitative behavior of the achievable throughput under the critical regime depends on whether the buffer size is greater than 1.

Method for providing channel list and display apparatus applying the same

Pilot-aided channel estimation has been popular for 4G wideband communication systems. Even though it is convenient, its limitation comes from the fact that the performance is bounded by the density of pilot symbols. Increasing pilot symbols improves channel estimation quality, but it also hurts bandwidth efficiency. In this paper, we advocate data-aided channel estimation for 5G. It is potentially the only solution to improve channel estimation quality without increasing pilot density. In particular, we aim to answer two fundamental questions for data-aided channel estimation: (1) What is the optimal scheme for data-aided channel estimation? (2) How can we make the optimal scheme practical by reducing its complexity? We present how we tackle these problems of data-aided channel estimation and show that the proposed iterative scheme yields significant gain in long term evolution (LTE) signal demodulation.