고속 이동 환경에서 대규모 다중안테나 시스템에 관한 연구

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2020. 8. 이용환.Advanced cellular communication systems may obtain high array gain by employing massive multi-input multi-output (m-MIMO) systems, which may require accurate channel state information (CSI). When users are in high mobility, it may not be easy to get accurate CSI. When we transmit signal to users in high mobility, we may experience serious performance loss due to the inaccuracy of outdated CSI, associated with so-called channel aging effect. This problem may be alleviated by exploiting channel correlation matrix (CCM) in spatial domain. However, it may require an additional process for the estimation of CCM, which may require high signaling overhead in m-MIMO environments. In this dissertation, we consider signal transmission to multiple users in high mobility in m-MIMO environments. We consider the estimation of CSI with reduced signaling overhead. The signaling overhead for the CSI estimation is a challenging issue in m-MIMO environments. We may reduce the signaling overhead for the CSI estimation by using pilot signal transmitted by means of beamforming with a weight determined by eigenvectors of CCM. To this end, we need to estimate the CCM, which may still require large signaling overhead. We consider the estimation of CCM with antennas in a uniform linear array (ULA). Since pairs of antennas with an equal distance may experience spatial channel correlation similar to each other in ULA antenna environments, we may jointly estimate the spatial channel correlation. We estimate the mean-square error (MSE) of elements of estimated CCM and then discard the elements whose MSE is higher than a reference value for the improvement of CCM estimation. We may estimate the CSI from the estimated CCM with reduced signaling overhead. We consider signal transmission robust to the presence of channel aging effect. Users in different mobility may differently experience the channel aging effect. This means that they may differently suffer from transmission performance loss. To alleviate this problem, we transmit signal to maximize the average signal-to-leakage-plus-noise ratio, making it possible to individually handle the channel aging effect. We consider the signal transmission to the eigen-direction of a linear combination of CSI and CCM. Analyzing the transmission performance in terms of signal-to-interference-plus-noise ratio, we control the transmit power by using an iterative water-filling technique. Finally, we consider the allocation of transmission resource in the presence of channel aging effect. We design a sub-optimal greedy algorithm that allocates the transmission resource to maximize the sum-rate in the presence of channel aging effect. We may estimate the sum-rate from the beam weight and a hypergeometric function (HF) that represents the effect of outdated CSI on the transmission performance. However, it may require very high computational complexity to calculate the beam weight and the HF in m-MIMO environments. To alleviate the complexity problem, we determine the beam weight in dominant eigen-direction of CCM and approximate the HF as a function of temporal channel correlation. Since we may estimate the sum-rate by exploiting spatial and temporal channel correlation, we may need to update the resource allocation only when the change of CCM or temporal channel correlation is large enough to affect the sum-rate. Simulation results show that the proposed scheme provides performance similar to a greedy algorithm based on accurate sum-rate, while significantly reducing the computational complexity.기지국이 수많은 안테나를 활용하여 높은 전송 이득을 얻을 수 있는 대규모 다중 안테나(massive MIMO) 시스템이 차세대 무선 통신 시스템으로 각광받고 있다. 이를 위해서는 정확한 채널 정보(channel state information)를 기반으로 하는 신호 전송 및 자원 관리 기술이 필수적이다. 하지만 사용자가 고속으로 이동하는 환경에서는 기지국이 추정한 채널 정보와 실제 전송 채널이 크게 달라지는 채널 변화 효과(channel aging effect)가 발생하여, 시스템 전송 성능이 심각하게 하락할 수 있다. 위 문제를 해결하기 위하여, 상대적으로 사용자 이동성에 느리게 변화하는 공간 상관도 행렬(channel correlation matrix)을 활용할 수 있다. 하지만 대규모 다중 안테나 시스템에서는 기지국이 공간 상관도 행렬을 추정하는 과정에서 큰 파일럿(pilot) 신호 부담이 발생할 수 있다. 본 논문은 고속 이동 환경에서의 대규모 다중 안테나 시스템에서 다중 사용자에 대한 신호 전송을 고려한다. 우선, 낮은 파일럿 신호 부담을 갖는 채널 정보 추정 방법을 제안한다. 대규모 다중 안테나 시스템에서 채널 정보 추정은 큰 파일럿 신호 부담을 야기할 수 있다. 이때 공간 상관도 행렬을 활용한 파일럿 신호 설계를 통하여 채널 정보 추정으로 인한 신호 부담을 효과적으로 감소시킬 수 있다. 하지만 이를 위해서는 공간 상관도 행렬을 추정해야 하며, 이 과정에서 큰 신호 부담이 야기될 수 있다. 제안 기법은 기지국이 균일한 선형 안테나 배열(uniform linear array)을 가지고 있는 환경에서, 같은 거리의 안테나 쌍들의 채널 간 공간 상관도가 유사하다는 특징을 활용하여, 상기 안테나 쌍들의 채널 간 공간 상관도를 최소자승추정법(least-square estimation)을 활용하여 추정한다. 그리고 추정된 공간 상관도의 평균제곱오차(mean-square error)를 추정하여, 상기 평균제곱오차가 큰 공간 상관도를 0으로 치환하여 공간 상관도 행렬의 추정 정확도를 높인다. 또한 상기 추정한 공간 상관도 행렬을 활용하여 낮은 신호 부담으로 채널 정보를 추정할 수 있는 것을 보인다. 둘째로, 사용자 이동성에 의한 채널 변화에 강인한 신호 전송 방법을 제안한다. 사용자들이 서로 다른 속도로 이동하는 환경에서는 채널 변화에 의한 신호 전송 성능 저하 역시 사용자마다 다르게 나타날 수 있다. 위 문제를 해결하기 위하여, 각 사용자에 대한 채널 변화 효과를 개별적으로 고려하면서 평균 신호 대 누수간섭 및 잡음비(signal-to-leakage-plus-noise ratio)를 최대화하는 전송 빔 가중치를 설계한다. 제안 기법은 사용자들의 채널 정보와 공간 상관도 행렬의 선형 결합의 고유방향(eigen-direction)으로 신호를 전송한다. 또한 제안 기법을 사용할 때의 신호 대 간섭 및 잡음비(signal-to-interference-plus-noise ratio)를 분석하고, 이를 기반으로 하는 전송 전력 분배 방법을 제안한다. 끝으로, 사용자 이동성에 따른 채널 변화를 고려하는 자원 할당 방법을 제안한다. 이를 위하여, 상기 채널 변화를 고려하여 시스템 전송 성능(sum-rate)을 최대화하는 탐욕(greedy) 알고리듬 기반의 자원 할당 기술을 설계한다. 고속 이동 환경에서 시스템 전송 성능을 추정하기 위해서는 사용자들에 대한 전송 빔 가중치와 행렬에 대한 초기하 함수(hypergeometric function of a matrix argument)와 관련된 복잡한 연산이 필요하다. 이 문제를 해결하기 위하여, 빔 가중치를 공간 상관도 행렬의 고유방향으로 결정하고, 초기하 함수를 채널 시간 상관도에 대한 함수로 근사한다. 상기 전송 성능 추정 방법이 채널의 공간 및 시간 상관도에만 의존한다는 점을 활용하여, 채널 공간 및 시간 상관도가 크게 변화한 사용자가 존재할 때에 한하여 사용자들에 대한 자원 할당 상태를 갱신하는 방법을 제안한다. 실험을 통하여, 제안 기법이 복잡한 시스템 전송 성능을 기반으로 하는 자원 할당 방법과 유사한 자원 할당 성능을 보이면서도 계산 복잡도를 획기적으로 줄이는 것을 보인다.Abstract i Contents v List of Figures vii List of Tables ix Chapter 1. Introduction 1 Chapter 2. M-MIMO systems in the presence of channel aging effect 9 Chapter 3. Estimation of channel correlation matrix 13 3.1. Previous works 14 3.2. Proposed scheme 19 3.3. Performance evaluation 29 Chapter 4. Mobility-aware signal transmission in m-MIMO systems 43 4.1. Previous works 44 4.2. Proposed scheme 46 4.3. Performance evaluation 62 Chapter 5. Mobility-aware resource allocation in m-MIMO systems 73 5.1. Sum-rate-based greedy algorithm 74 5.2. Proposed scheme 76 5.3. Performance evaluation 88 Chapter 6. Conclusions 99 Appendix 103 References 105 Korean Abstract 115 Acknowledgement 119Docto

Impact of Channel Aging on Massive MIMO Vehicular Networks in Non-isotropic Scattering Scenarios

Massive multiple-input multiple-output (MIMO) relies on accurate channel estimation for precoding and receiving to achieve its claimed performance advantages. When serving vehicular users, the rapid channel aging effect greatly hinders its advantages, and a careful system design is required to ensure an efficient use of wireless resources. In this paper, we investigate this problem for the first time in a non-isotropic scattering scenario. The von Mises distribution is adopted for the angle of arrival (AoA), resulting in a tunable channel temporal correlation coefficient (TCC) model, which can adapt to different AoA spread conditions through the k parameter and incorporates the isotropic Jakes-Clarke model as a special case. The simulated results in a Manhattan grid-type multi-cell network clearly demonstrate the impact of channel aging on the uplink spectral efficiency (SE) performance and moreover, in order to maximize the area average SE, the size of the transmission block should be optimally selected according to some linear equations of k

Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions

Massive MIMO is a compelling wireless access concept that relies on the use of an excess number of base-station antennas, relative to the number of active terminals. This technology is a main component of 5G New Radio (NR) and addresses all important requirements of future wireless standards: a great capacity increase, the support of many simultaneous users, and improvement in energy efficiency. Massive MIMO requires the simultaneous processing of signals from many antenna chains, and computational operations on large matrices. The complexity of the digital processing has been viewed as a fundamental obstacle to the feasibility of Massive MIMO in the past. Recent advances on system-algorithm-hardware co-design have led to extremely energy-efficient implementations. These exploit opportunities in deeply-scaled silicon technologies and perform partly distributed processing to cope with the bottlenecks encountered in the interconnection of many signals. For example, prototype ASIC implementations have demonstrated zero-forcing precoding in real time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing of 8 terminals). Coarse and even error-prone digital processing in the antenna paths permits a reduction of consumption with a factor of 2 to 5. This article summarizes the fundamental technical contributions to efficient digital signal processing for Massive MIMO. The opportunities and constraints on operating on low-complexity RF and analog hardware chains are clarified. It illustrates how terminals can benefit from improved energy efficiency. The status of technology and real-life prototypes discussed. Open challenges and directions for future research are suggested.Comment: submitted to IEEE transactions on signal processin

Energy Efficient Massive MIMO and Beamforming for 5G Communications

Massive multiple-input multiple-output (MIMO) has been a key technique in the next generation of wireless communications for its potential to achieve higher capacity and data rates. However, the exponential growth of data traffic has led to a significant increase in the power consumption and system complexity. Therefore, we propose and study wireless technologies to improve the trade-off between system performance and power consumption of wireless communications. This Thesis firstly proposes a strategy with partial channel state information (CSI) acquisition to reduce the power consumption and hardware complexity of massive MIMO base stations. In this context, the employment of partial CSI is proposed in correlated communication channels with user mobility. By exploiting both the spatial correlation and temporal correlation of the channel, our analytical results demonstrate significant gains in the energy efficiency of the massive MIMO base station. Moreover, relay-aided communications have experienced raising interest; especially, two-way relaying systems can improve spectral efficiency with short required operating time. Therefore, this Thesis focuses on an uncorrelated massive MIMO two-way relaying system and studies power scaling laws to investigate how the transmit powers can be scaled to improve the energy efficiency up to several times the energy efficiency without power scaling while approximately maintaining the system performance. In a similar line, large antenna arrays deployed at the space-constrained relay would give rise to the spatial correlation. For this reason, this Thesis presents an incomplete CSI scheme to evaluate the trade-off between the spatial correlation and system performance. In addition, the advantages of linear processing methods and the effects of channel aging are investigated to further improve the relay-aided system performance. Similarly, large antenna arrays are required in millimeter-wave communications to achieve narrow beams with higher power gain. This poses the problem that locating the best beam direction requires high power and complexity consumption. Therefore, this Thesis presents several low-complexity beam alignment methods with respect to the state-of-the-art to evaluate the trade-off between complexity and system performance. Overall, extensive analytical and numerical results show an improved performance and validate the effectiveness of the proposed techniques

Optimum Averaging of Superimposed Training Schemes in OFDM under Realistic Time-Variant Channels

The current global bandwidth shortage in orthogonal frequency division multiplexing (OFDM)-based systems motivates the use of more spectrally efficient techniques. Superimposed training (ST) is a candidate in this regard because it exhibits no information rate loss. Additionally, it is very flexible to deploy and it requires low computational cost. However, data symbols sent together with training sequences cause an intrinsic interference. Previous studies, based on an oversimplified channel (a quasi-static channel model) have solved this interference by averaging the received signal over the coherence time. In this paper, the mean square error (MSE) of the channel estimation is minimized in a realistic time-variant scenario. The optimization problem is stated and theoretical derivations are presented to attain the optimum amount of OFDM symbols to be averaged. The derived optimal value for averaging is dependent on the signal-to-noise ratio (SNR) and it provides a better MSE, of up to two orders of magnitude, than the amount given by the coherence time. Moreover, in most cases, the optimal number of OFDM symbols for averaging is much shorter, about 90% reduction of the coherence time, thus it provides a decrease of the system delay. Therefore, these results match the goal of improving performance in terms of channel estimation error while getting even better energy efficiency, and reducing delays.This work was supported by the Spanish National Project Hybrid Terrestrial/Satellite Air Interface for 5G and Beyond - Areas of Dif-cult Access (TERESA-ADA) [Ministerio de Economía y Competitividad (MINECO)/Agencia Estatal de Investigación (AEI)/Fondo Europeo de Desarrollo Regional (FEDER), Unión Europea (UE)] under Grant TEC2017-90093-C3-2-R

An efficient reconfigurable optimal source detection and beam allocation algorithm for signal subspace factorization

Now a days, huge amount of data is communicated through channels in wireless network. It requires an efficient parallel operation for the optimal utilization of frequency, time allocation and coding model for signal subspace factorization in smart antenna. In view of this requirement, an efficient reconfigurable optimal source detection and beam allocation algorithm (RoSDBA) is proposed. The proposed algorithm is able to allocate desired signal to the user space to reduce the noise and also for efficient allocation of subspace to remove disturbance in all directions. The proposed method efficiently utilizes the antenna array elements by accurate identification and allocation of antenna array elements such as individual radiators, radiation beam, signal strength, and disturbance factor. With respect to simulation analysis, the proposed method shows better performance for the resolution, radiation beam allocations, identification bias, distribution factor and time taken for the detection of various array arrangements and source numbers