Exploring Alternative Massive MIMO Designs : Superimposed Pilots and Mixed-ADCs

Abstract

This is a Swedish Doctor of Philosophy Dissertation. The Doctor of Philosophy degree comprises 240 ECTS credits of postgraduate studies.Cover: A Massive MIMO network where the stairs in the buildings represent the different ADC bit resolutions in a mixed-ADC design. The two merging signals from cellular phones illustrate the superposition of pilot and data signals, corresponding to the superimposed pilots design. This cover was painted by Andrea Britto Moreno with design input from the author. Exploring Alternative Massive MIMO Designs AbstractThe development of information and communication technologies (ICT) provides the means for reaching global connectivity that can help humanity progress and prosper. This comes with high demands on data traffic and number of connected devices which are rapidly growing and need to be met by technological development. Massive MIMO, where MIMO stands for multiple-input multiple-output, is a fundamental component of the 5G wireless communication standard for its ability to provide high spectral and energy efficiency, SE and EE, respectively. The key feature of this technology is the use of a large number of antennas at the base stations (BSs) to spatially multiplex several user equipments (UEs).In the development of new technologies like Massive MIMO, many design alternatives need to be evaluated and compared in order to find the best operating point with a preferable tradeoff between low cost and complexity. In this thesis, two alternative designs for signal processing and hardware in Massive MIMO are studied and compared with the baseline operation in terms of SE, EE, and power consumption. The first design is called superimposed pilot (SP) transmission and is based on superimposing pilot and data symbols to eliminate the need to reserve dedicated time-frequency resources for pilots. This allows more data to be transmitted and supports longer pilot sequences that, in turn, reduce pilot contamination. The second design is mixed analog-to-digital converters (ADCs) and it aims at balancing the SE performance and the power consumption cost by allowing different ADC bit resolutions across the BS antennas.The results show that the Massive MIMO baseline, when properly optimized, is the preferred choice in standard deployments and propagation conditions. However, the SP alternative design can increase the SE compared to the baseline by using the Massive-MIMO iterative channel estimation and decoding (MICED) algorithm proposed in this dissertation. In particular, the SE gains are found in cases with high mobility, high carrier frequencies, or high number of spatially multiplexed UEs. For the mixed-ADCs alternative design, improvements in the SE and EE compared to the Massive vii MIMO baseline can be achieved in cases with distributed BS antennas where interference suppression techniques are used. ix 3.2.2 Optimal Tradeoff between HWIs and BS Antennas . . 82 3.2.3 Optimal HWI Allocation under i.i.d. Rayleigh Fading 85 3.2.4 Optimal HWI Allocation under Correlated Rayleigh Fading and LSF...

Nearest Neighbor Decoding and Pilot-Aided Channel Estimation for Fading Channels

“…While the capacity pre-log of general point-to-point MIMO fading channels remains an open problem, the capacity pre-log of point-to-point MISO fading channels is known, cf. (22). It thus follows that, for n r = n t,1 = n t,2 = 1, we have…”

“…Thus, in this case nearest neighbor decoding together with pilot-aided channel estimation achieves the capacity pre-log of MISO fading channels (22) as well as the lower bound on the capacity pre-log of MIMO fading channels (24). Suppose that both transmitter and receiver use the same number of antennas, namely, n t n r min(n t , n r ).…”

“…Observe that (24) specializes to (22) for n r = 1. It should be noted that the capacity pre-log for MISO and SISO fading channels was derived under a peak-power constraint on the channel inputs, whereas the lower bound on the capacity pre-log for MIMO fading channels was derived under an average-power constraint.…”

“…For MIMO channels, the above scheme achieves the best so far known lower bound on the capacity pre-log obtained in [ 12 ]. The proof steps followed in this paper apply also to other pilot-assisted communication strategies and can be mimicked to perform rigorous analyses of their achievable rates; see, e.g., [ 19 , 20 , 21 , 22 ].…”