Multi-Antenna Users in Cell-Free Massive MIMO: Stream Allocation and Necessity of Downlink Pilots

We consider a cell-free massive multiple-input multiple-output (MIMO) system with multiple antennas on the users and access points (APs). In previous works, the downlink spectral efficiency (SE) has been evaluated using the hardening bound that requires no downlink pilots. This approach works well for single-antenna users. In this paper, we show that much higher SEs can be achieved if downlink pilots are sent when having multi-antenna users. The reason is that the effective channel matrix does not harden. We propose a pilot-based downlink estimation scheme, derive a new SE expression, and show numerically that it yields substantially higher performance when having correlated Rayleigh fading channels. In cases with multi-antenna users, the APs can either transmit the same or different data streams. The latter reduces the fronthaul signaling but comes with a SE loss. We propose precoding and combining schemes for these cases and consider whether channel knowledge is shared between the APs. Finally, we show numerically how the number of users, APs, and the number of antennas on users and APs affect the SE.

Downlink Pilots are Essential for Cell-Free Massive MIMO with Multi-Antenna Users

We consider a cell-free massive MIMO system with multiple antennas on the users and access points. In previous works, the downlink spectral efficiency (SE) has been evaluated using the hardening bound that requires no downlink pilots. This approach works well when having single-antenna users. In this paper, we show that much higher SEs can be achieved if downlink pilots are sent since the effective channel matrix does not harden when having multi-antenna users. We propose a pilot-based downlink estimation scheme and derive a new SE expression that utilizes zero-forcing combining. We show numerically how the number of users and user antennas affects the SE.

Symplectic Transformations on Wigner Distributions and Time Frequency Signal Design

This work considers uncertainty relations on time frequency distributions from a signal processing viewpoint. An uncertainty relation on the marginalizable time frequency distributions is given. A result from quantum mechanics is used on Wigner distributions and marginalizable time frequency distributions to investigate the change in variance of time and frequency variables from a signal processing perspective. Moreover, operations on signals which leave uncertainty relations unchanged are studied.

Uncertainty Relations for MIMO Ambiguity Functions

In this paper, uncertainty relations for MIMO ambiguity functions are given. Norm inequalities on the MIMO ambiguity functions in terms of signals of concern are studied. A signal dependent lower bound on the support of MIMO ambiguity functions is given via application of a local uncertainty relation. The uncertainty of Lieb and MIMO ambiguity functions are related. Uncertainty relations on MIMO covariance matrix are given in terms of matrix norms.

MIMO Ambiguity Functions and Harmonic Analysis

Multi input multi output (MIMO) systems\' capability of using seperate signals brings many advantages to radar signal processing and time frequency analysis. In this paper, a variety of properties of MIMO ambiguity functions related with representations of Heisenberg group are given. Some of the existing results for SIMO ambiguity functions are generalized to MIMO case. Combined effect of seperate signals is investigated.