Multi-user MIMO beamforming:implementation, verification in L1 capacity, and performance testing

Abstract. A certain piece of technology takes a lot of effort, research, and testing to reach the productisation phase. Radio features are implemented in layer 1 (L1) before moving to the hardware implementation phase, where their functioning is tested and verified. The target of the thesis is to implement and verify beamforming based multi-user multiple-input multiple-output (MU-MIMO) in L1 capacity and performance testing (PET) environment. The L1 testing environment mainly focuses on 4G and 5G stand-alone (SA) cases, while the focus of this thesis work is only on 5G SA technology, which features beamforming and MU-MIMO. Beamforming and MU-MIMO have been tested in an end-to-end system but not specifically in L1. The L1 testing provides a deeper analysis of beamforming and MU-MIMO in L1 and aids in problem identification at an early productisation phase, saving both time and money. L1 PET has multiple components that work together for L1 data transmission in both uplink (UL) and downlink (DL) directions and handle the verification of the transmitted data. The main components that play a key role in the implementation of multi-user MIMO beamforming concern frame design setup, message setup for UL and DL using correct channels and interfaces, transmission of the generated data in UL and DL, and message capturing at L1 end (whether correct messages are transmitted or not). For verification purposes, methods such as analysing plots from L1 log results based on comparison with radio specifications are used to determine whether the generated test output is correct or not. Finally, performance metrics, such as error vector magnitude (EVM), UE per transmission time interval (TTI), number of layers per UE, channel quality indicator (CQI), physical resource block (PRB) count, and throughput, are evaluated to assess the capacity and performance correctness of the implemented test setup

Provisioning statistical QoS for coordinated communications with limited feedback

The capacity performance of ICIC has been extensively studied in coordinated multi-point transmissions (CoMP). In practice however, due to limited feedback, the acquired channel direction information (CDI), which is crucial for ICIC, is often partially available. Hence one may question whether the ICIC is able to meet the Quality-of-Service (QoS) requirements. This paper considers the optimal partitioning of the feedback bits in CoMP while accounting for the inter-cell interference cancellation (ICIC). In this paper, we adopt a statistical model of QoS in CoMP by using the notion of effective capacity (EC). Utilizing EC we then formulate the system function as an optimization problem with the objective of maximizing the total EC subject to the limited feedback available to the cluster of base stations (BSs). Analytical bounds are then obtained on the EC performance which are then utilized as the base for algorithms that assign feedback bits among the user equipments (UEs) and BSs. Using simulations we then investigate the accuracy of the obtained bounds and highlight practical system designs for dealing with stringent delay requirements. Of crucial practical importance, the findings of this paper also indicates that in CoMP there is an optimal cluster size for a given feedback capacity that maximizes the corresponding EC

Downlink Achievable Rate Analysis for FDD Massive MIMO Systems

Multiple-Input Multiple-Output (MIMO) systems with large-scale transmit antenna arrays, often called massive MIMO, are a very promising direction for 5G due to their ability to increase capacity and enhance both spectrum and energy efficiency. To get the benefit of massive MIMO systems, accurate downlink channel state information at the transmitter (CSIT) is essential for downlink beamforming and resource allocation. Conventional approaches to obtain CSIT for FDD massive MIMO systems require downlink training and CSI feedback. However, such training will cause a large overhead for massive MIMO systems because of the large dimensionality of the channel matrix. In this dissertation, we improve the performance of FDD massive MIMO networks in terms of downlink training overhead reduction, by designing an efficient downlink beamforming method and developing a new algorithm to estimate the channel state information based on compressive sensing techniques. First, we design an efficient downlink beamforming method based on partial CSI. By exploiting the relationship between uplink direction of arrivals (DoAs) and downlink direction of departures (DoDs), we derive an expression for estimated downlink DoDs, which will be used for downlink beamforming. Second, By exploiting the sparsity structure of downlink channel matrix, we develop an algorithm that selects the best features from the measurement matrix to obtain efficient CSIT acquisition that can reduce the downlink training overhead compared with conventional LS/MMSE estimators. In both cases, we compare the performance of our proposed beamforming method with traditional methods in terms of downlink achievable rate and simulation results show that our proposed method outperform the traditional beamforming methods

Performance Analysis and Mitigation Techniques for I/Q-Corrupted OFDM Systems

Orthogonal Frequency Division Multiplexing (OFDM) has become a widely adopted modulation technique in modern communications systems due to its multipath resilience and low implementation complexity. The direct conversion architecture is a popular candidate for low-cost, low-power, fully integrated transceiver designs. One of the inevitable problems associated with analog signal processing in direct conversion involves the mismatches in the gain and phases of In-phase (I) and Quadrature-phase (Q) branches. Ideally, the I and Q branches of the quadrature mixer will have perfectly matched gains and are orthogonal in phase. Due to imperfect implementation of the electronics, so called I/Q imbalance emerges and creates interference between subcarriers which are symmetrically apart from the central subcarrier. With practical imbalance levels, basic transceivers fail to maintain the sufficient image rejection, which in turn can cause interference with the desired transmission. Such an I/Q distortion degrades the systems performance if left uncompensated. Moreover, the coexistence of I/Q imbalance and other analog RF imperfections with digital baseband and higher layer functionalities such as multiantenna transmission and radio resource management, reduce the probability of successful transmission. Therefore, mitigation of I/Q imbalance is an essential substance in designing and implementing modern communications systems, while meeting required performance targets and quality of service. This thesis considers techniques to compensate and mitigate I/Q imbalance, when combined with channel estimation, multiantenna transmission, transmission power control, adaptive modulation and multiuser scheduling. The awareness of the quantitative relationship between transceiver parameters and system parameters is crucial in designing and dimensioning of modern communications systems. For this purpose, analytical models to evaluate the performance of an I/Q distorted system are considered