Reciprocity Calibration for Massive MIMO: Proposal, Modeling and Validation

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

Spectral Efficiency of One-Bit Sigma-Delta Massive MIMO

We examine the uplink spectral efficiency of a massive MIMO base station employing a one-bit Sigma-Delta ( \Sigma \Delta ) sampling scheme implemented in the spatial rather than the temporal domain. Using spatial rather than temporal oversampling, and feedback of the quantization error between adjacent antennas, the method shapes the spatial spectrum of the quantization noise away from an angular sector where the signals of interest are assumed to lie. It is shown that, while a direct Bussgang analysis of the \Sigma \Delta approach is not suitable, an alternative equivalent linear model can be formulated to facilitate an analysis of the system performance. The theoretical properties of the spatial quantization noise power spectrum are derived for the \Sigma \Delta array, as well as an expression for the spectral efficiency of maximum ratio combining (MRC). Simulations verify the theoretical results and illustrate the significant performance gains offered by the \Sigma \Delta approach for both MRC and zero-forcing receivers

Millimeter Wave Antenna Array Calibration and Validation for 5G New Radio Access

This Master thesis work was performed in Ericsson AB, Lund. It studies and validates two classes of algorithms to be used in mm-wave massive MIMO antenna arrays, for their use in the future 5G mobile communication systems. The first class of algorithms relates to the calibration of the transceiver (TRX) chains responses of the antenna array and makes use of the antenna array mutual coupling, which is considered as known by the system. It is used to compensate for inaccuracies in the TRX base-band complex responses, caused by environmental conditions such as temperature, humidity and aging, which are much more critical in mm-wave than conventional bands. After the calibration, the beamforming capabilities of the massive MIMO systems are increased. The second class of algorithms is related to the estimation of antenna array mutual coupling matrix, due to the fact that this information is used in the first method. The antenna array mutual coupling estimation algorithm was proposed by Ericsson's engineers and tested in this work. Since the systems considered will work at mm-wave frequencies, small construction errors can create big differences in antenna array coupling properties, so the coupling matrix must be estimated for each constructed system of the same kind. Several estimation and calibration algorithms were simulated, using Matlab® as a software for simulation, and analyzed. The estimation of TRX chains' complex responses is needed. Two estimation algorithms are used, referred as linear and non-linear least squares estimation. These estimation algorithms need to use the information regarding the antenna array mutual coupling matrix and over-the-air (OTA) self-measurements between pairs of elements in the antenna array. These measurements can be done considering all the possible pairs of elements in the antenna array (full measurements) or just a subset of the closest pairs (neighbour measurements). Firstly, simulations using a generic case were done, and later, simulations considering constraints in an Ericsson radio module proprietary system were done. Internal and external unwanted interference in the radio system were considered, to check for limitations in the estimation algorithms. So as to validate the proposed methods and algorithms, a testbed system using a radio module working at 28 GHz was built and measured. The signal levels and frequencies in the HW components of the testbed were calculated using the data-sheets of the components and later measured using a vector network analyzer and an spectrum analyzer. The last task was to write the code for controlling the radio module, then perform calibration using it and finally measure the performance of the algorithm using an an-echoic chamber. Due to a lack of time, the code needed to do the OTA measurements, the OTA measurements and the validation of the algorithms are left as future work. Observing the results of the simulations, several recommendations are made for future measurement validations. One common conclusion is that it is best to perform the minimum amount of self-measurements available, with those being the ones corresponding to the strongest coupling gains between elements in the antenna array. There were different preferred algorithms for calibration depending on the value of the signal-to-noise ratio (SNR) and the value of the signal-to-interference (SIR) ratio. Regarding the antenna array coupling matrix estimation, the conclusion is that the algorithm proposed by Ericsson's engineers works, but in order to achieve good results, the required post-processing SNR values of the related measurements may be too big. Therefore, it may take too long to perform these measurements. Possibilities to improve this algorithm are recommended and left as future work. Regarding the HW to be used in the testbed, it is recommended to add some extra components in order to improve the quality of the signals in the system, for future measurements.Do you remember a time when you were watching a standard definition (SD) YouTube video or streaming a song on your laptop or PC and the player suddenly stopped? Nowadays you want to watch streaming videos on your laptop or mobile phone in a high-definition (1080p) format and in the future you may even want to stream 4K 3D videos and watch them in your Smart-TV or mobile phone. Mobile services are expected to be fast, reliable and cheap. Apart from this, the number of connected devices is growing exponentially, and three times more devices are expected to be connected in the next 5 years. Consequently, scientists and engineers are working towards developing and installing increasingly sophisticated systems to meet today's and tomorrow's user demands. When it comes to cellular communications, there are several ideas on how to improve the network performance. Two of them are to have base stations with a lot of cooperating antennas and to use higher frequency bandwidths, only available at higher frequencies, in the millimeter wave region. These two concepts seem complicated, and they are! Nevertheless, these novel technologies are two main candidates to be integrated in future fifth-generation (5G) mobile systems, expected to be rolled-out in 2020. When using multiple antennas in a base station (or even in a mobile device), it is desirable to avoid different behavior of the circuits in the system over time caused by temperature, humidity and other environmental factors. This is even more important when many antennas are used, as slight changes in the circuit responses may destroy the performance advantage of using these cooperating antennas. Everything gets even more complicated in higher frequencies, since the environmental effect is stronger. But Maths are really strong, and since all the data in our devices is in fact processed mathematically in a digital form, can't we do something to compensate for this physical (i.e. analog) effects in the mathematical (i.e. digital) domain?. The answer is yes, we can, and this mathematical compensation process is called calibration. For the calibration procedure (or algorithm) to work, it is necessary to know how the many antennas interrelate to one another, for the different frequencies in the frequency band of interest. Hence, some antenna factory characterization must be done beforehand. Since this characterization gets more and more complex with an increasing number of antennas, and the antenna properties may still vary after installation, it is necessary to find more efficient methods of characterization (in particular, efficient estimators of massive MIMO arrays coupling matrix). This Master thesis addresses these two problems associated with environmental changes effects in mm-wave massive MIMO systems and characterization of massive MIMO arrays