42 research outputs found

    Reciprocity Calibration for Massive MIMO: Proposal, Modeling and Validation

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    This paper presents a mutual coupling based calibration method for time-division-duplex massive MIMO systems, which enables downlink precoding based on uplink channel estimates. The entire calibration procedure is carried out solely at the base station (BS) side by sounding all BS antenna pairs. An Expectation-Maximization (EM) algorithm is derived, which processes the measured channels in order to estimate calibration coefficients. The EM algorithm outperforms current state-of-the-art narrow-band calibration schemes in a mean squared error (MSE) and sum-rate capacity sense. Like its predecessors, the EM algorithm is general in the sense that it is not only suitable to calibrate a co-located massive MIMO BS, but also very suitable for calibrating multiple BSs in distributed MIMO systems. The proposed method is validated with experimental evidence obtained from a massive MIMO testbed. In addition, we address the estimated narrow-band calibration coefficients as a stochastic process across frequency, and study the subspace of this process based on measurement data. With the insights of this study, we propose an estimator which exploits the structure of the process in order to reduce the calibration error across frequency. A model for the calibration error is also proposed based on the asymptotic properties of the estimator, and is validated with measurement results.Comment: Submitted to IEEE Transactions on Wireless Communications, 21/Feb/201

    Analysis and Mitigation of Channel Non-Reciprocity in TDD MIMO Systems

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    The ever-growing demands for higher number of connected devices as well as higher data rates and more energy eļ¬ƒcient wireless communications have necessitated the use of new technical solutions. One of the main enablers in this respect is Multiple-Input Multiple-Output (MIMO) systems in which transmitting and receiving sides are equipped with multiple antennas. Such systems need precise information of the MIMO radio channel available at the transmitter side to reach their full potential. Owing to the reciprocity of uplink and downlink channels in Time Division Duplexing (TDD) systems, Base Stations (BSs) may acquire the required channel state information for downlink transmission by processing the received uplink pilots. However, such reciprocity only applies to the physical propagation channels and does not take into consideration the so-called observable or eļ¬€ective uplink and downlink channels which also include the possible non-reciprocal behavior of the involved transceiver circuits and antenna systems. This thesis focuses on the channel non-reciprocity problem in TDD MIMO systems due to mismatches in Frequency Response (FR) and mutual coupling of transmitting and receiving chains of transceivers and associated antenna systems. The emphasis in the work and developments is placed on multi-user MIMO precoded downlink transmission. In this respect, the harmful impacts of channel non-reciprocity on the performance of such downlink transmission are analyzed. Additionally, non-reciprocity mitigation methods are developed seeking to reclaim TDD reciprocity and thus to avoid the involved performance degradations. Firstly, the focus is on the small-scale MIMO systems where BSs are equipped with relatively limited number of antennas, say in the order of 4 to 8. The provided analysis on Zero-Forcing (ZF) and eigen-based precoding schemes in single-cell scenario shows that both schemes experience considerable performance degradations in the presence of FR and mutual coupling mismatches. Whereas, in general, the system performance is more sensitive to i) non-reciprocity sources in the BS transceiver; and ii) mutual coupling mismatches. Then, assuming reasonably good antenna isolation, an Over-The-Air (OTA) pilot-based algorithm is proposed to eļ¬ƒciently mitigate the BS transceiver non-reciprocity. The numerical results indicate high accuracy in estimating the BS transceiver non- reciprocity parameters as well as considerable improvement in the performance of the system. In multi-cell scenario, both centralized and decentralized precoding approaches are covered while the focus is on the impacts of FR mismatches of UE transceivers. The how that there is severe degradation in the performance of decentralized precoding while centralized precoding is immune to such channel non-reciprocity impacts. Secondly, the so-called massive MIMO systems are considered in which the number of antennas in the BS side is increased with an order of magnitude or more. Based on the detailed developed signal models, closed-form analytical expressions are ļ¬rst provided for eļ¬€ective signal-to-interference-plus-noise ratios of both ZF and maximum ratio transmission precoding schemes. The analysis covers the joint impacts of channel non-reciprocity and imperfect uplink channel estimation and shows that while both precoding schemes suļ¬€er from channel non-reciprocity impacts, ZF is more sensitive to such non-idealities. Next, a concept and an algorithm are proposed, involving UE side measurements and processing, to be deployed in the UE side to eļ¬ƒciently estimate the level of BS transceiver non-reciprocity. This enables the UEs to inform the BS about the optimum time to perform channel non-reciprocity mitigation round and thus improves the spectral eļ¬ƒciency. Finally, in order to mitigate channel non-reciprocity in massive MIMO systems, an eļ¬ƒcient iterative OTA pilot-based algorithm is proposed which estimates and mitigates transceiver non-reciprocity impacts in both BS and UE sides. Compared to the state-of-the-art methods, the simulation results indicate substantial improvements in system spectral eļ¬ƒciency when the proposed method is being used. Overall, the analyses provided in this thesis can be used as valuable tools to better understand practical TDD MIMO systems which can be very helpful in designing such systems. Furthermore, the channel non-reciprocity mitigation methods proposed in this thesis can be deployed in practical TDD MIMO syst channel reciprocity and thus signiļ¬cantly increase the spectral eļ¬ƒciency

    Cell-Free Multi-User Massive MIMO Under Channel Non-Reciprocity

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    In Cell-Free (CF) Massive multiple-input multiple-output (MIMO), a large number of access points (AP) are geographically distributed over the coverage area, and jointly serve a smaller number of users on the same time/frequency resources. In this thesis, we study the impact of non-reciprocal channels (NRC) and imperfect channel state information (CSI) on Cell-Free massive MIMO systems performance. As non-reciprocity sources, we consider transceiver frequency response mismatches and mutual-coupling mismatches in uplink and downlink analogue processing chains. We study both single-antenna and multi-antenna AP configurations, and in this last case, we also include non-reciprocal mutual coupling in addition to transceiver frequency responses. We present a novel non-reciprocal channel model based on experimental results from massive MIMO reciprocity calibration tests. Previous models consider that channel non-reciprocity characteristics are fast-varying like random variables; conversely, we consider a model where non-reciprocity values change substantially slower in time, as demonstrated in experimental results. Besides, we derive closed-form analytical expressions of capacity lower bounds for zero-forcing and conjugate beamforming schemes. The conclusion is that non-reciprocal channels can be a limiting factor for Cell-Free systems performance; nevertheless, only AP mismatches impact on performance while UE mismatches do not affect performance. Furthermore, only phase non-reciprocity degrades MRT performance, whereas both phase and amplitude non-reciprocity degrade ZF performance. Therefore, calibration requirements may dispense with amplitude compensation when APs use MRT scheme, and prioritise phase over amplitude compensation when APs use ZF scheme. Mutual coupling considerately affects both MRT and ZF precoders, but ZF to a greater extent. Hence, calibration procedures should always try to compensate for mutual coupling non-reciprocity

    An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications

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    To meet the future demand for huge traffic volume of wireless data service, the research on the fifth generation (5G) mobile communication systems has been undertaken in recent years. It is expected that the spectral and energy efficiencies in 5G mobile communication systems should be ten-fold higher than the ones in the fourth generation (4G) mobile communication systems. Therefore, it is important to further exploit the potential of spatial multiplexing of multiple antennas. In the last twenty years, multiple-input multiple-output (MIMO) antenna techniques have been considered as the key techniques to increase the capacity of wireless communication systems. When a large-scale antenna array (which is also called massive MIMO) is equipped in a base-station, or a large number of distributed antennas (which is also called large-scale distributed MIMO) are deployed, the spectral and energy efficiencies can be further improved by using spatial domain multiple access. This paper provides an overview of massive MIMO and large-scale distributed MIMO systems, including spectral efficiency analysis, channel state information (CSI) acquisition, wireless transmission technology, and resource allocation

    Multi-Antenna Techniques for Next Generation Cellular Communications

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    Future cellular communications are expected to offer substantial improvements for the pre- existing mobile services with higher data rates and lower latency as well as pioneer new types of applications that must comply with strict demands from a wider range of user types. All of these tasks require utmost efficiency in the use of spectral resources. Deploying multiple antennas introduces an additional signal dimension to wireless data transmissions, which provides a significant alternative solution against the plateauing capacity issue of the limited available spectrum. Multi-antenna techniques and the associated key enabling technologies possess unquestionable potential to play a key role in the evolution of next generation cellular systems. Spectral efficiency can be improved on downlink by concurrently serving multiple users with high-rate data connections on shared resources. In this thesis optimized multi-user multi-input multi-output (MIMO) transmissions are investigated on downlink from both filter design and resource allocation/assignment points of view. Regarding filter design, a joint baseband processing method is proposed specifically for high signal-to-noise ratio (SNR) conditions, where the necessary signaling overhead can be compensated for. Regarding resource scheduling, greedy- and genetic-based algorithms are proposed that demand lower complexity with large number of resource blocks relative to prior implementations. Channel estimation techniques are investigated for massive MIMO technology. In case of channel reciprocity, this thesis proposes an overhead reduction scheme for the signaling of user channel state information (CSI) feedback during a relative antenna calibration. In addition, a multi-cell coordination method is proposed for subspace-based blind estimators on uplink, which can be implicitly translated to downlink CSI in the presence of ideal reciprocity. Regarding non-reciprocal channels, a novel estimation technique is proposed based on reconstructing full downlink CSI from a select number of dominant propagation paths. The proposed method offers drastic compressions in user feedback reports and requires much simpler downlink training processes. Full-duplex technology can provide up to twice the spectral efficiency of conventional resource divisions. This thesis considers a full-duplex two-hop link with a MIMO relay and investigates mitigation techniques against the inherent loop-interference. Spatial-domain suppression schemes are developed for the optimization of full-duplex MIMO relaying in a coverage extension scenario on downlink. The proposed methods are demonstrated to generate data rates that closely approximate their global bounds

    Hierarchical-Absolute Reciprocity Calibration for Millimeter-wave Hybrid Beamforming Systems

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    In time-division duplexing (TDD) millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the reciprocity mismatch severely degrades the performance of the hybrid beamforming (HBF). In this work, to mitigate the detrimental effect of the reciprocity mismatch, we investigate reciprocity calibration for the mmWave-HBF system with a fully-connected phase shifter network. To reduce the overhead and computational complexity of reciprocity calibration, we first decouple digital radio frequency (RF) chains and analog RF chains with beamforming design. Then, the entire calibration problem of the HBF system is equivalently decomposed into two subproblems corresponding to the digital-chain calibration and analog-chain calibration. To solve the calibration problems efficiently, a closed-form solution to the digital-chain calibration problem is derived, while an iterative-alternating optimization algorithm for the analog-chain calibration problem is proposed. To measure the performance of the proposed algorithm, we derive the Cram\'er-Rao lower bound on the errors in estimating mismatch coefficients. The results reveal that the estimation errors of mismatch coefficients of digital and analog chains are uncorrelated, and that the mismatch coefficients of receive digital chains can be estimated perfectly. Simulation results are presented to validate the analytical results and to show the performance of the proposed calibration approach

    System capacity enhancement for 5G network and beyond

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    A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Doctor of PhilosophyThe demand for wireless digital data is dramatically increasing year over year. Wireless communication systems like Laptops, Smart phones, Tablets, Smart watch, Virtual Reality devices and so on are becoming an important part of peopleā€™s daily life. The number of mobile devices is increasing at a very fast speed as well as the requirements for mobile devices such as super high-resolution image/video, fast download speed, very short latency and high reliability, which raise challenges to the existing wireless communication networks. Unlike the previous four generation communication networks, the fifth-generation (5G) wireless communication network includes many technologies such as millimetre-wave communication, massive multiple-input multiple-output (MIMO), visual light communication (VLC), heterogeneous network (HetNet) and so forth. Although 5G has not been standardised yet, these above technologies have been studied in both academia and industry and the goal of the research is to enhance and improve the system capacity for 5G networks and beyond by studying some key problems and providing some effective solutions existing in the above technologies from system implementation and hardware impairmentsā€™ perspective. The key problems studied in this thesis include interference cancellation in HetNet, impairments calibration for massive MIMO, channel state estimation for VLC, and low latency parallel Turbo decoding technique. Firstly, inter-cell interference in HetNet is studied and a cell specific reference signal (CRS) interference cancellation method is proposed to mitigate the performance degrade in enhanced inter-cell interference coordination (eICIC). This method takes carrier frequency offset (CFO) and timing offset (TO) of the userā€™s received signal into account. By reconstructing the interfering signal and cancelling it afterwards, the capacity of HetNet is enhanced. Secondly, for massive MIMO systems, the radio frequency (RF) impairments of the hardware will degrade the beamforming performance. When operated in time duplex division (TDD) mode, a massive MIMO system relies on the reciprocity of the channel which can be broken by the transmitter and receiver RF impairments. Impairments calibration has been studied and a closed-loop reciprocity calibration method is proposed in this thesis. A test device (TD) is introduced in this calibration method that can estimate the transmittersā€™ impairments over-the-air and feed the results back to the base station via the Internet. The uplink pilots sent by the TD can assist the BS receiversā€™ impairment estimation. With both the uplink and downlink impairments estimates, the reciprocity calibration coefficients can be obtained. By computer simulation and lab experiment, the performance of the proposed method is evaluated. Channel coding is an essential part of a wireless communication system which helps fight with noise and get correct information delivery. Turbo codes is one of the most reliable codes that has been used in many standards such as WiMAX and LTE. However, the decoding process of turbo codes is time-consuming and the decoding latency should be improved to meet the requirement of the future network. A reverse interleave address generator is proposed that can reduce the decoding time and a low latency parallel turbo decoder has been implemented on a FPGA platform. The simulation and experiment results prove the effectiveness of the address generator and show that there is a trade-off between latency and throughput with a limited hardware resource. Apart from the above contributions, this thesis also investigated multi-user precoding for MIMO VLC systems. As a green and secure technology, VLC is achieving more and more attention and could become a part of 5G network especially for indoor communication. For indoor scenario, the MIMO VLC channel could be easily ill-conditioned. Hence, it is important to study the impact of the channel state to the precoding performance. A channel state estimation method is proposed based on the signal to interference noise ratio (SINR) of the usersā€™ received signal. Simulation results show that it can enhance the capacity of the indoor MIMO VLC system

    Modeling and Linearization of MIMO RF Transmitters

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    Multiple-input multiple-output (MIMO) technology will continue to play a vital role in next-generation wireless systems, e.g., the fifth-generation wireless networks (5G). Large-scale antenna arrays (also called massive MIMO) seem to be the most promising physical layer solution for meeting the ever-growing demand for high spectral efficiency. Large-scale MIMO arrays are typically deployed with high integration and using low-cost components. Hence, they are prone to different hardware impairments such as crosstalk between the transmit antennas and power amplifier (PA) nonlinearities, which distort the transmitted signal. To avert the performance degradation due to these impairments, it is essential to have mechanisms for predicting the output of the MIMO arrays. Such prediction mechanisms are mandatory for performance evaluation and, more importantly, for the adoption of proper compensation techniques such as digital predistortion (DPD) schemes. This has stirred a considerable amount of interest among researchers to develop new hardware and signal processing solutions to address the requirements of large-scale MIMO systems. In the context of MIMO systems, one particular problem is that the hardware cost and complexity scale up with the increase of the size of the MIMO system. As a result, the MIMO systems tend to be implemented on a chip and are very compact. Reduction of the cost by reducing the bill of material is possible when several components are eliminated. The reuse of already existing hardware is an alternative solution. As a result, such systems are prone to excessive sources of distortion, such as crosstalk. Accordingly, crosstalk in MIMO systems in its simplest form can affect the DPD coefficient estimation scheme. In this thesis, the effect of crosstalk on two main DPD estimation techniques, know as direct learning algorithm (DLA) and indirect learning algorithm (ILA), is studied. The PA behavioral modeling and DPD scheme face several challenges that seek cost-efficient and flexible solutions too. These techniques require constant capture of the PA output feedback signal, which ultimately requires the implementation of a complete transmitter observation receiver (TOR) chain for the individual transmit path. In this thesis, a technique to reuse the receiver path of the MIMO TDD transceiver as a TOR is developed, which is based on over-the-air (OTA) measurements. With these techniques, individual PA behavioral modeling and DPD can be done by utilizing a few receivers of the MIMO TDD system. To use OTA measurements, an on-site antenna calibration scheme is developed to individually estimate the coupling between the transmitter and the receiver antennas. Furthermore, a digital predistortion technique for compensating the nonlinearity of several PAs in phased arrays is presented. The phased array can be a subset of massive MIMO systems, and it uses several antennas to steer the transmitted signal in a particular direction by appropriately assigning the magnitude and the phase of the transmitted signal from each antenna. The particular structure of phased arrays requires the linearization of several PAs with a single DPD. By increasing the number of RF branches and consequently increasing the number of PAs in the phased array, the linearization task becomes challenging. The DPD must be optimized to results in the best overall linear performance of the phased array in the field. The problem of optimized DPD for phased array has not been addressed appropriately in the literature. In this thesis, a DPD technique is developed based on an optimization problem to address the linearization of PAs with high variations. The technique continuously optimizes the DPD coefficients through several iterations considering the effect of each PA simultaneously. Therefore, it results in the best optimized DPD performance for several PAs. Extensive analysis, simulations, and measurement evaluation is carried out as a proof of concept. The different proposed techniques are compared with conventional approaches, and the results are presented. The techniques proposed in this thesis enable cost-efficient and flexible signal processing approaches to facilitate the development of future wireless communication systems
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