Dongwoon Bai

LTE-advanced modem design: challenges and perspectives

The commercial deployment of LTE Release 8 is gaining significant momentum all over the globe, and LTE is evolving to LTE-Advanced, which offers various new features to meet or exceed IMT-Advanced requirements. Since LTE-Advanced targets ambitious spectral efficiency and peak throughput, it poses tremendous system design challenges to operators and manufacturers, especially for mobile terminals. This article discusses modem design issues related to carrier aggregation, enhanced ICIC for HetNet, detection of eight-layer transmission, reference signals for enhanced multi-antenna support, and HARQ buffer management. We provide an overview of technical challenges and sketch the perspectives for tackling them to exploit the full benefits of the LTE-Advanced system.

Rate of Channel Hardening of Antenna Selection Diversity Schemes and Its Implication on Scheduling

For a multiple-antenna system, we find a simple and accurate expression for the asymptotic distribution of the antenna selection gain when the transmitter selects the transmit antenna with the strongest channel. We use this to estimate the underlying channel capacity distributions and obtain the approximate ergodic capacity. This estimate is compared with upper and lower bounds. This analysis demonstrates that unlike multiple-input/multiple-output (MIMO) systems, the channel for antenna selection systems hardens at a slower rate, and thus a significant multiuser scheduling gain can exist-Theta (1/logm) for channel selection as opposed to Theta (1/radicm) for MIMO, where m is the number of transmit antennas.

Near ML Modulation Classification

This paper deals with the problem of classification of digital modulation. In particular, we develop and propose a practical modulation classification scheme based on the likelihood of observations. While ML classification is well known and shows the optimal performance, its computational complexity prevents it from being easily implemented in hardware. On the contrary, our proposed scheme has low computational complexity and near optimal classification performance. Moreover, this scheme is designed to perform in fast fading channels. It is shown that our proposed classifier takes advantage of the channel variation without loosing near optimality.

Channel Hardening and the Scheduling Gain of Antenna Selection Diversity Schemes

For a multiple antenna system, we compute the asymptotic distribution of antenna selection gain when the transmitter selects the transmit antenna with the strongest channel. We use this to asymptotically estimate the underlying channel capacity distributions, and demonstrate that unlike multiple- input/multiple-output (MIMO) systems,the channel for antenna selection systems hardens at a slower rate, and thus a significant multiuser scheduling gain can exist. Additionally, even without this scheduling gain, it is demonstrated that transmit antenna selection systems outperform open loop MIMO systems at low signal-to-interference-plus-noise ratio (SINR) regimes, particularly for small number of receive antennas. This may have some implications on wireless system design, because most of the users in modern wireless systems have low SINRs.

Rate and UE Selection Algorithms for Interference-Aware Receivers

In cellular communications, user equipment (UE, i.e., mobile device)-side interference cancellation (IC) along with multicell coordinated scheduling can significantly reduce the effect of the downlink intercell interference. To aid UE-side IC, a study item, called network-assisted interference cancellation and suppression (NAICS), has been initiated for Long Term Evolution (LTE) Advanced Release 12. Among NAICS receivers, this paper considers a receiver with interference-aware successive decoding (IASD) capability, which is one of the most advanced UE-side IC techniques. The IASD achievable transmission rate is dependent on the interferer transmission rate. Thus, coordination among multiple cells for rate and UE selection would be necessary for the overall network performance enhancement. In this paper, we consider a single dominant interference model and propose an optimal single-user rate selection algorithm based on the belief-propagation framework. In the multi-user-per-cell case we propose several UE and rate selection algorithms and analyze their performance.

Systematic pruning of blind decoding results

In LTE downlink control channel, a large number of blind decoding attempts are made while the number of valid codewords is limited. The blind decoding results are then verified using a 16-bit CRC. However, even with the 16-bit CRC, the false alarm (FA) rate of such blind decoding is inevitably high. This paper investigates the problem of pruning of blind decoding results to reduce the FA rate. To the best of our knowledge, the approach using a soft correlation metric (SCM) shows the best FA reduction performance among existing schemes. However, following the Bayes principle, we propose novel likelihood-based pruning that provides systematic balancing between the FA rate and the miss (MS) rate. Moreover, the SNR gain of our likelihood-based pruning is shown to be around 1 dB with respect to SCM-based pruning in AWGN channel. The proposed likelihood-based approach can be applied to any error-correction/detection systems whose decoders make many blind decoding attempts.

Performance Analysis of a PASD Antenna System in Rayleigh Fading Channels

In this paper, we analyze the performance of a communication system that employs Protocol Assisted Switched Diversity (PASD) antennas under Rayleigh fading channel conditions. The PASD system accumulates time-displaced blocks, each with the same information but using different antennas, and then combines their symbols using maximal ratio combining (MRC). In the PASD system, quality of service (QoS) is ensured by comparing the available signal-to-noise ratio (SNR) at the output of the combiner against a preset threshold value. Our analysis shows that this method reduces the number of transmissions significantly as the channel deteriorates as compared with ARQ without memory while it can satisfy the symbol error rate (SER) requirement for most of blocks. It is also shown that deploying more than one antenna is important to stabilize the system when the channel becomes static.

Mutual Information Bounds for MIMO Gaussian Channels

The mutual information between modulation- constrained input and its output through Gaussian channels has been studied for various purposes such as physical layer abstraction. While the capacity of multiple-input and multiple-output (MIMO) Gaussian channels is well understood and its simple formula exists, this modulation- constrained mutual information for MIMO Gaussian channels has only been computed numerically and its expression for online computation has not been found. To tackle this challenge, this paper proposes several new bounds on the mutual information for MIMO Gaussian channels, which can be used for approximation. The proposed bounds are expressed in the forms that can be computed online. Moreover, these bounds are improved by taking a minimum of upper bounds and a maximum of lower bounds. The proposed bounds are compared with the mutual information obtained through simulation.

On the Capacity Limit of Wireless Channels Under Colored Scattering

It has been generally believed that the multiple-input multiple-output channel capacity grows linearly with the size of antenna arrays. In terms of degrees of freedom, linear transmit and receive arrays of length L in a scattering environment of total angular spread \Ω\ asymptotically have \Ω\L degrees of freedom. In this paper, it is claimed that the linear increase in degrees of freedom may not be attained when scattered electromagnetic fields in the underlying scattering environment are statistically correlated. After introducing a model of correlated scattering, which is referred to as the colored scattering model, we derive a capacity upper bound, assuming that the channel is known perfectly at the receiver and in distribution at the transmitter. Unlike the uncorrelated case, the prelog factor of the capacity, i.e., the number of degrees of freedom, in the colored scattering channel is asymptotically limited by \Ω\·min{L, 1/ ΓI} where Γ is a parameter determining the extent of correlation. In other words, for very large arrays in the colored scattering environment, degrees of freedom can get saturated to an intrinsic limit rather than increasing linearly with the array size.

Mismatched hypothesis testing with application to digital modulation classification

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.