Seunghyeong Yoo

In a complete theory there is an element corresponding to each element of reality. A sufficient condition for the reality of a physical quantity is the possibility of predicting it with certainty, without disturbing the system. In quantum mechanics in the case of two physical quantities described by non-commuting operators, the knowledge of one precludes the knowledge of the other. Then either (1) the description of reality given by the wave function in quantum mechanics is not complete or (2) these two quantities cannot have simultaneous reality. Consideration of the problem of making predictions concerning a system on the basis of measurements made on another system that had previously interacted with it leads to the result that if (1) is false then (2) is also false. One is thus led to conclude that the description of reality as given by a wave function is not complete.

We propose a max-min fairness (MMF) precoding algorithm for a multi-user multiple-input multiple-output (MU-MIMO) downlink system with different user weights, considering the quantization effects of low-resolution digital-to-analog converters (DACs). To find a precoder, we first formulate a problem, which jointly considers MMF and quantization. This joint problem presents some challenges that make finding a direct solution infeasible: non-smoothness and non-convexity. To address the non-smoothness, we use LogSumExp method to approximate the problem into a smooth problem. Subsequently, we derive the first-order optimality condition and cast it as a nonlinear eigenvalue problem. Lastly, we employ a generalized power iteration method to determine the superior stationary point. Simulation result demonstrates the superiority of our MMF precoding algorithm.

This paper investigates full-duplex (FD) multi-user multiple-input multiple-output (MU-MIMO) system design with coarse quantization. We first analyze the impact of self-interference (SI) on quantization in FD single-input single-output systems. The analysis elucidates that the minimum required number of analog-to-digital converter (ADC) bits is logarithmically proportional to the ratio of total received power to the received power of desired signals. Motivated by this, we design a FD MIMO beamforming method that effectively manages the SI. Dividing a spectral efficiency maximization beamforming problem into two sub-problems for alternating optimization, we address the first by optimizing the precoder: obtaining a generalized eigenvalue problem from the first-order optimality condition, where the principal eigenvector is the optimal stationary solution, and adopting a power iteration method to identify this eigenvector. Subsequently, a quantization-aware minimum mean square error combiner is computed for the derived precoder. Through numerical studies, we observe that the proposed beamformer reduces the minimum required number of ADC bits for achieving higher spectral efficiency than that of half-duplex (HD) systems, compared to FD benchmarks. The overall analysis shows that, unlike with quantized HD systems, more than 6 bits are required for the ADC to fully realize the potential of the quantized FD system.

Underwater acoustic (UWA) channel is one of the common systems for wireless underwater communication. However, the underwater environment poses significant challenges to reliable and efficient communication. This paper is a survey on channel modeling for UWA communications. We investigate various UWA channel modeling approaches that incorporate both large- and small-scale fading effects and provides a comprehensive summary of the key findings.

Satellite communications offer the potential of ensuring global coverage with a substantial capacity. In this paper, we examine the coverage performance of satellite networks by considering a distance-dependent line-of-sight (LOS) and non-LOS (NLOS) channel propagation probability, which takes into account the shadowing effect. Building upon the stochastic geometry-based network analysis used for terrestrial networks, we employ a Poisson point process to model both the satellite network and its users. Through this approach, we derive a theoretical expression for the coverage probability with beam gain under a nearest satellite association rule, providing an analytical understanding of the satellite network. The accuracy of the derived expression is confirmed through simulation results. The derived expression encompasses various network parameters such as satellite density, altitude, channel fading, pathloss, LOS probability, and beam gain, offering valuable insights into satellite networks.

We consider a full-duplex (FD) multi-user multiple-input multiple-output (MU-MIMO) system with low-resolution quantizers at an access point (AP). In the considered FD system, there are main bottlenecks: self-interference (SI), co-channel interference (CCI), and quantization errors. In this paper, we propose a novel precoding and combining method to maximize the sum spectral efficiency (SE) by incorporating the effect of the quantization errors as well as the SI and CCI. Since the beamformers are intertwined with the quantization errors, SI, and CCI, it is highly challenging to solve the sum SE maximization problem. To address the challenges, we convert the problem into the Rayleigh quotient form. Then, we derive the first-order optimality condition with interpreting it as a generalized eigenvalue problem by leveraging the principle of the Rayleigh quotient problem. Accordingly, we adopt a power iteration method for identifying the leading eigenvector: the best local optimal precoding solution. Consequently, we propose an alternating algorithm to jointly optimize the precoder and combiner. Simulations validate the proposed algorithm.