Power saving and optimal hybrid precoding in millimeter wave massive MIMO systems for 5G

The proliferation of wireless services emerging from use cases offifth-generation(5G) technology is posing many challenges on cellular communicationinfrastructure. They demand to connect a massive number of devices withenhanced data rates. The massive multiple-input multiple-output (MIMO)technology at millimeter-wave (mmWave) in combination with hybrid precodingemerges as a concrete tool to address the requirements of 5G networkdevelopments. But Massive MIMO systems consume significant power fornetwork operations. Hence the prior role is to improve the energy efficiency byreducing the power consumption. This paper presents the power optimizationmodels for massive MIMO systems considering perfect channel state information(CSI) and imperfect CSI. Further, this work proposes an optimal hybrid precodingsolution named extended simultaneous orthogonal matchingpursuit (ESOMP).Simulation results reveal that a constant sum-rate can be achieved in massiveMIMO systems while significantly reducing the power consumption. Theproposed extended SOMPhybrid precoder performsclose to the conventionaldigital beamforming method. Further, modulation schemes compatible withmassive MIMO systems are outlined and their bit error rate (BER) performance isinvestigate

FDD Massive MIMO Based on Efficient Downlink Channel Reconstruction

Massive multiple-input multiple-output (MIMO) systems deploying a large number of antennas at the base station considerably increase the spectrum efficiency by serving multiple users simultaneously without causing severe interference. However, the advantage relies on the availability of the downlink channel state information (CSI) of multiple users, which is still a challenge in frequency-division-duplex transmission systems. This paper aims to solve this problem by developing a full transceiver framework that includes downlink channel training (or estimation), CSI feedback, and channel reconstruction schemes. Our framework provides accurate reconstruction results for multiple users with small amounts of training and feedback overhead. Specifically, we first develop an enhanced Newtonized orthogonal matching pursuit (eNOMP) algorithm to extract the frequency-independent parameters (i.e., downtilts, azimuths, and delays) from the uplink. Then, by leveraging the information from these frequency-independent parameters, we develop an efficient downlink training scheme to estimate the downlink channel gains for multiple users. This training scheme offers an acceptable estimation error rate of the gains with a limited pilot amount. Numerical results verify the precision of the eNOMP algorithm and demonstrate that the sum-rate performance of the system using the reconstructed downlink channel can approach that of the system using perfect CSI

FDD Massive MIMO Based on Efficient Downlink Channel Reconstruction

This paper focuses on frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems and proposes a transceiver design that fully exploits the downlink spatial multiplexing gain with only a small amount of overhead. The bottleneck lies in the acquisition of downlink channel state information (CSI), which occurs when large scale antenna array is employed in FDD transmission systems. Fortunately, the spatial reciprocity between uplink and downlink inspires us to reconstruct the downlink channel based on the frequency-independent parameters (downtilts, azimuths and delays) that can be derived in the uplink. We first extract these parameters through an enhanced Newtonized orthogonal matching pursuit (e-NOMP) algorithm which is proposed in this paper to fit the massive MIMO orthogonal frequency division multiplexing (OFDM) system. After formulating the requirement to achieve an acceptable estimation error rate, we propose a low-cost downlink training scheme to estimate the downlink gains of each user channel. This scheme saves the training time resource by introducing a predefined spatial angle grid which corresponds to a beam set and by minimizing the number of selected beams which is equal to the number of OFDM symbols used for downlink training. Having obtained the reconstructed multiuser channel, the BS can maximize the spatial multiplexing gain by serving all the users simultaneously without causing severe interference. Numerical results verify the precision of the e-NOMP algorithm, and demonstrate that sum-rate performance of the reconstructionbased transceiver design approximates that of using perfect CSI

대규모 다중 안테나 환경에서 낮은 복잡도의 다중 사용자 신호전송에 관한 연구

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·컴퓨터공학부, 2020. 8. 이용환.Advanced wireless communication systems may employ massive multi-input multi-output (m-MIMO) techniques for performance improvement. A base station equipped with an m-MIMO configuration can serve a large number of users by means of beamforming. The m-MIMO channel becomes asymptotically orthogonal to each other as the number of antennas increases to infinity. In this case, we may optimally transmit signal by means of maximum ratio transmission (MRT) with affordable implementation complexity. However, the MRT may suffer from inter-user interference in practical m-MIMO environments mainly due to the presence of insufficient channel orthogonality. The use of zero-forcing beamforming can be a practical choice in m-MIMO environments since it can easily null out inter-user interference. However, it may require huge computational complexity for the generation of beam weight. Moreover, it may suffer from performance loss associated with the interference nulling, referred to transmission performance loss (TPL). The TPL may become serious when the number of users increases or the channel correlation increases in spatial domain. In this dissertation, we consider complexity-reduced multi-user signal transmission in m-MIMO environments. We determine the beam weight to maximize the signal-to-leakage plus noise ratio (SLNR) instead of signal-to-interference plus noise ratio (SINR). We determine the beam direction assuming combined use of MRT and partial ZF that partially nulls out interference. For further reduction of computational complexity, we determine the beam weight based on the approximated SLNR. We consider complexity-reduced ZF beamforming that generates the beam weight in a group-wise manner. We partition users into a number of groups so that users in each group experience low TPL. We approximately estimate the TPL for further reduction of computational complexity. Finally, we determine the beam weight for each user group based on the approximated TPL.차세대 무선 통신 시스템에서 성능 향상을 위해 대규모 다중 안테나 (massive MIMO) 기술들을 사용할 수 있다. 대규모 안테나를 가진 기지국은 많은 수의 사용자들을 빔포밍 (beamforming)으로 서비스해줄 수 있다. 안테나 수가 무한히 증가함에 따라서 채널은 점근적으로 서로 직교 (orthogonal)하게 된다. 이러한 경우, 낮은 실장 복잡도를 가지는 최대 비 전송 (maximum ratio transmission)을 사용함으로써 신호전송을 최적화할 수 있다. 하지만, 현실적인 대규모 다중 안테나 환경에서는 채널 직교성이 충분하지 못하기 때문에 최대 비 전송은 간섭에 의한 성능 저하를 겪을 수 있다. 제로-포싱 (zero-forcing) 빔포밍은 간섭을 쉽게 제거할 수 있기 때문에 대규모 다중 안테나 환경에서 현실적인 선택이 될 수 있다. 하지만, 제로-포싱은 빔 가중치 (beam weight) 생성으로 인해 높은 계산 복잡도를 요구할 수 있다. 뿐만 아니라, 제로-포싱은 간섭 제거에 대한 대가로 심각한 성능 저하 (즉, transmission performance loss; TPL)를 겪을 수 있다. TPL은 사용자 수가 많거나 채널의 공간 상관도가 클 때 더 심각해질 수 있다. 본 논문에서 대규모 다중 안테나 환경에서 낮은 복잡도의 다중 사용자 신호전송을 고려한다. 제안 기법은 신호-대-간섭 및 잡음 비 (signal-to-interference plus noise ratio) 대신 신호-대-유출 및 잡음 비 (signal-to-leakage plus noise ratio)를 최대화하는 빔 가중치를 결정한다. 제안 기법은 최대 비 전송과 간섭을 선택적으로 제거하는 부분 제로-포싱 (partial zero-forcing)의 사용을 기반으로 빔 방향을 결정한다. 계산 복잡도를 더 감소시키기 위해서, 제안 기법은 근사화된 신호-대-유출 및 잡음비를 사용하여 빔 가중치를 결정한다. 본 논문에서 그룹 기반으로 빔 가중치를 생성하는 낮은 복잡도의 제로-포싱 빔포밍 전송을 고려한다. 제안 기법은 사용자들이 낮은 TPL을 갖도록 사용자들을 다수의 그룹으로 분리시킨다. 계산 복잡도를 더 감소시키기 위해서, 제안 기법은 TPL을 근사적으로 추정한다. 마지막으로, 제안 기법은 근사화된 TPL을 기반으로 형성된 각 사용자 그룹에 대하여 빔 가중치를 결정한다.Chapter 1. Introduction 1 Chapter 2. System model 10 Chapter 3. Complexity-reduced multi-user signal transmission 15 3.1. Previous works 15 3.2. Proposed scheme 24 3.3. Performance evaluation 47 Chapter 4. User grouping-based ZF transmission 57 4.1. Spatially correlated channel 57 4.2. Previous works 59 4.3. Proposed scheme 66 4.4. Performance evaluation 87 Chapter 5. Conclusions and further research issues 94 Appendix 97 A. Proof of Lemma 3-4 97 B. Proof of Lemma 3-5 100 C. Proof of strict quasi-concavity of SLNR_(k) 101 References 103 Korean Abstract 115Docto

Radio Resource Management for New Application Scenarios in 5G: Optimization and Deep Learning

The fifth-generation (5G) New Radio (NR) systems are expected to support a wide range of emerging applications with diverse Quality-of-Service (QoS) requirements. New application scenarios in 5G NR include enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable low-latency communications (URLLC). New wireless architectures, such as full-dimension (FD) massive multiple-input multiple-output (MIMO) and mobile edge computing (MEC) system, and new coding scheme, such as short block-length channel coding, are envisioned as enablers of QoS requirements for 5G NR applications. Resource management in these new wireless architectures is crucial in guaranteeing the QoS requirements of 5G NR systems. The traditional optimization problems, such as subcarriers and user association, are usually non-convex or Non-deterministic Polynomial-time (NP)-hard. It is time-consuming and computing-expensive to find the optimal solution, especially in a large-scale network. To solve these problems, one approach is to design a low-complexity algorithm with near optimal performance. In some cases, the low complexity algorithms are hard to obtain, deep learning can be used as an accurate approximator that maps environment parameters, such as the channel state information and traffic state, to the optimal solutions. In this thesis, we design low-complexity optimization algorithms, and deep learning frameworks in different architectures of 5G NR to resolve optimization problems subject to QoS requirements. First, we propose a low-complexity algorithm for a joint cooperative beamforming and user association problem for eMBB in 5G NR to maximize the network capacity. Next, we propose a deep learning (DL) framework to optimize user association, resource allocation, and offloading probabilities for delay-tolerant services and URLLC in 5G NR. Finally, we address the issue of time-varying traffic and network conditions on resource management in 5G NR

A Study on Three Dimensional Spatial Scattering Modulation Systems

With an explosive growth of data traffic demand, the researchers of the mobile communication era forecast that the traffic volume will have a 1000x increase in the forthcoming beyond fifth generation (B5G) network. To satisfy the growing traffic demand, the three-dimensional (3-D) multiple-input-and-multiple-output (MIMO) system is considered as a key technology to enhance spectrum efficiency (SE), which explores degrees of freedom in both the vertical and the horizontal dimensions. Combined with 3-D MIMO technology, index modulation (IM) is proposed to improve both energy efficiency (EE) and SE in the B5G era. Existing IM technologies can be categorized according to the domain in which the additional IM bits are modulated, e.g., the spatial-domain IM, the frequency-domain IM and the beamspace-domain IM etc. As one of the mainstream IM techniques, spatial scattering modulation (SSM) is proposed, which works in the beamspace-domain. For SSM systems, the information bits are denoted by the distinguishable signal scattering paths and the modulated symbols. Therein, two information bit streams are transmitted simultaneously by selections of modulated symbols and scattering paths. However, the existing papers only discuss two-dimensional (2-D) SSM systems. The 2-D SSM system applies linear antenna arrays, which only take the azimuth angles to recognise the direction of scattering paths. Therefore, to take the full advantage of the beamspace-domain resources, this thesis mainly focuses on the 3-D SSM system design and the performance evaluation. Firstly, a novel 3-D SSM system is designed. For the 3-D SSM system, besides the azimuth angles of arrival (AoA) and angles of departure (AoD), the elevation AoA and AoD are considered. Then the optimum detection algorithm is obtained, and the closed-form union upper bound expression on average bit error probability (ABEP) is derived. Moreover, the system performance is evaluated under a typical indoor environment. Numerical results indicate that the novel 3-D SSM system outperforms the conventional 2-D SSM system, which reduces the ABEP by 10 times with the same signal-to-noise ratio (SNR) level under the typical indoor environment. Secondly, for the system equipped with large-scale antenna arrays, hybrid beamforming schemes with several RF-chains have attracted more attention. To further explore the throughput of the 3-D SSM system, a generalised 3-D SSM system is proposed, which generates several RF-chains in a transmission time slot to convey modulated symbols. A system model of generalised 3-D SSM is proposed at first. Then an optimum detection algorithm is designed. Meanwhile, a closed-form expression of the ABEP is also derived and validated by Monte-Carlo simulation. For the performance evaluation, three stochastic propagation environments with randomly distributed scatterers are adopted. The results reveal that the generalised 3-D SSM system has better ABEP performance compared with the system with a single RF-chain. Considering different propagation environments, the SSM system has better ABEP performance under the statical propagation environments than the stochastic propagation environments. Thirdly, to reduce the hardware and computational complexities, two optimisation schemes are proposed for the generalised 3-D SSM systems. The 2-D fast Fourier transform (FFT) based transceivers are designed to improve the hardware friendliness, which replace the analogue phase shift networks by the multi-bit phase shifter networks. To reduce the computational complexity of the optimum detection algorithm, a low-complexity detection scheme is designed based on the linear minimum mean square error (MMSE) algorithm. Meanwhile, to quickly evaluate, the asymptotic ABEP performance and the diversity gain of the generalised 3-D SSM system are obtained