Distributed Linear Precoding and User Selection in Coordinated Multicell Systems

In this manuscript we tackle the problem of semi-distributed user selection with distributed linear precoding for sum rate maximization in multiuser multicell systems. A set of adjacent base stations (BS) form a cluster in order to perform coordinated transmission to cell-edge users, and coordination is carried out through a central processing unit (CU). However, the message exchange between BSs and the CU is limited to scheduling control signaling and no user data or channel state information (CSI) exchange is allowed. In the considered multicell coordinated approach, each BS has its own set of cell-edge users and transmits only to one intended user while interference to non-intended users at other BSs is suppressed by signal steering (precoding). We use two distributed linear precoding schemes, Distributed Zero Forcing (DZF) and Distributed Virtual Signal-to-Interference-plus-Noise Ratio (DVSINR). Considering multiple users per cell and the backhaul limitations, the BSs rely on local CSI to solve the user selection problem. First we investigate how the signal-to-noise-ratio (SNR) regime and the number of antennas at the BSs affect the effective channel gain (the magnitude of the channels after precoding) and its relationship with multiuser diversity. Considering that user selection must be based on the type of implemented precoding, we develop metrics of compatibility (estimations of the effective channel gains) that can be computed from local CSI at each BS and reported to the CU for scheduling decisions. Based on such metrics, we design user selection algorithms that can find a set of users that potentially maximizes the sum rate. Numerical results show the effectiveness of the proposed metrics and algorithms for different configurations of users and antennas at the base stations.Comment: 12 pages, 6 figure

Robust leakage-based distributed precoder for cooperative multicell systems

Coordinated multipoint (CoMP) from long term evolution (LTE)-advanced is a promising technique to enhance the system spectral efficiency. Among the CoMP techniques, joint transmission has high communication requirements, because of the data sharing phase through the backhaul network, and coordinated scheduling and beamforming reduces the backhaul requirements, since no data sharing is necessary. Most of the available CoMP techniques consider perfect channel knowledge at the transmitters. Nevertheless for practical systems this is unrealistic. Therefore in this study the authors address this limitation by proposing a robust precoder for a multicell-based systems, where each base station (BS) has only access to an imperfect local channel estimate. They consider both the case with and without data sharing. The proposed precoder is designed in a distributed manner at each BS by maximising the signal-to-leakage-and-noise ratio of all jointly processed users. By considering the channel estimation error in the design of the precoder, they are able to reduce considerably the impact of these errors in the system's performance. The results show that the proposed scheme has improved performance especially for the high signal-to-noise ratio regime, where the impact of the channel estimation error may be more pronounced

Novel transmission and beamforming strategies for multiuser MIMO with various CSIT types

In multiuser multi-antenna wireless systems, the transmission and beamforming strategies that achieve the sum rate capacity depend critically on the acquisition of perfect Channel State Information at the Transmitter (CSIT). Accordingly, a high-rate low-latency feedback link between the receiver and the transmitter is required to keep the latter accurately and instantaneously informed about the CSI. In realistic wireless systems, however, only imperfect CSIT is achievable due to pilot contamination, estimation error, limited feedback and delay, etc. As an intermediate solution, this thesis investigates novel transmission strategies suitable for various imperfect CSIT scenarios and the associated beamforming techniques to optimise the rate performance. First, we consider a two-user Multiple-Input-Single-Output (MISO) Broadcast Channel (BC) under statistical and delayed CSIT. We mainly focus on linear beamforming and power allocation designs for ergodic sum rate maximisation. The proposed designs enable higher sum rate than the conventional designs. Interestingly, we propose a novel transmission framework which makes better use of statistical and delayed CSIT and smoothly bridges between statistical CSIT-based strategies and delayed CSIT-based strategies. Second, we consider a multiuser massive MIMO system under partial and statistical CSIT. In order to tackle multiuser interference incurred by partial CSIT, a Rate-Splitting (RS) transmission strategy has been proposed recently. We generalise the idea of RS into the large-scale array. By further exploiting statistical CSIT, we propose a novel framework Hierarchical-Rate-Splitting that is particularly suited to massive MIMO systems. Third, we consider a multiuser Millimetre Wave (mmWave) system with hybrid analog/digital precoding under statistical and quantised CSIT. We leverage statistical CSIT to design digital precoder for interference mitigation while all feedback overhead is reserved for precise analog beamforming. For very limited feedback and/or very sparse channels, the proposed precoding scheme yields higher sum rate than the conventional precoding schemes under a fixed total feedback constraint. Moreover, a RS transmission strategy is introduced to further tackle the multiuser interference, enabling remarkable saving in feedback overhead compared with conventional transmission strategies. Finally, we investigate the downlink hybrid precoding for physical layer multicasting with a limited number of RF chains. We propose a low complexity algorithm to compute the analog precoder that achieves near-optimal max-min performance. Moreover, we derive a simple condition under which the hybrid precoding driven by a limited number of RF chains incurs no loss of optimality with respect to the fully digital precoding case.Open Acces

Optimality Properties, Distributed Strategies, and Measurement-Based Evaluation of Coordinated Multicell OFDMA Transmission

The throughput of multicell systems is inherently limited by interference and the available communication resources. Coordinated resource allocation is the key to efficient performance, but the demand on backhaul signaling and computational resources grows rapidly with number of cells, terminals, and subcarriers. To handle this, we propose a novel multicell framework with dynamic cooperation clusters where each terminal is jointly served by a small set of base stations. Each base station coordinates interference to neighboring terminals only, thus limiting backhaul signalling and making the framework scalable. This framework can describe anything from interference channels to ideal joint multicell transmission. The resource allocation (i.e., precoding and scheduling) is formulated as an optimization problem (P1) with performance described by arbitrary monotonic functions of the signal-to-interference-and-noise ratios (SINRs) and arbitrary linear power constraints. Although (P1) is non-convex and difficult to solve optimally, we are able to prove: 1) Optimality of single-stream beamforming; 2) Conditions for full power usage; and 3) A precoding parametrization based on a few parameters between zero and one. These optimality properties are used to propose low-complexity strategies: both a centralized scheme and a distributed version that only requires local channel knowledge and processing. We evaluate the performance on measured multicell channels and observe that the proposed strategies achieve close-to-optimal performance among centralized and distributed solutions, respectively. In addition, we show that multicell interference coordination can give substantial improvements in sum performance, but that joint transmission is very sensitive to synchronization errors and that some terminals can experience performance degradations.Comment: Published in IEEE Transactions on Signal Processing, 15 pages, 7 figures. This version corrects typos related to Eq. (4) and Eq. (28

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