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Archive | 2016

Models and Preliminaries

Thomas L. Marzetta; Erik G. Larsson; Hong Yang; Hien Quoc Ngo

This chapter introduces the basic signal and channel models to be used throughout the book. We use standard complex baseband representations of all signals and noise, with the implicit assumption that all signals are eventually modulated onto a carrier with frequency f c and wavelength λ = c/f c , where c is the speed of light. Also, unless stated explicitly, all Gaussian random variables are complex-valued and circularly symmetric; see Appendix A for a treatment of such variables. Single-Antenna Transmitter and Single-Antenna Receiver The wireless channel takes an input signal x ( t ), emitted by a transmit antenna, and yields an output signal y ( t ), observed at a receive antenna. The relation between x ( t ) and y ( t ) is linear, owing to the linearity of Maxwells equations. However, this relation generally is timevarying, since the transmitter, receiver, and other objects in the propagation environment may move relative to one another. Coherence Time The time during which the channel can be reasonably well viewed as time-invariant is called the coherence time and denoted by T c (measured in seconds). To relate T c to the characteristics of the physical propagation environment, we consider a simple two-path propagation model where a transmit antenna emits a signal x ( t ) that reaches the receiver both directly via a LoS path, and via a single specular reflection; see Figure 2.1(a). If both paths have unit strength, and the bandwidth of x ( t ) is small enough that time-delays can be approximated as phase shifts, then by the superposition principle the received signal is where d 1 and d 2 are the propagation path lengths defined in Figure 2.1(a). Suppose, for the sake of argument, that when the receiver is located as shown in Figure 2.1(a), d 1 / λ and d 2 / λ are integers. Then the two paths add up constructively and y ( t ) = 2 x ( t ). Next, if the receiver is displaced d meters to the right, so that we have the situation in Figure 2.1(b), the received signal will instead be The two paths add up destructively if the cosine in (2.2) is equal to zero. As shown in Figure 2.2(a), this occurs periodically for displacements d that are spaced λ /2 meters apart. The channel may be considered time-invariant as long as the receiver does not move farther than this distance, λ /2.


IEEE Transactions on Information Theory | 2018

Interference Reduction in Multi-Cell Massive MIMO Systems With Large-Scale Fading Precoding

Alexei Ashikhmin; Liangbin Li; Thomas L. Marzetta


Archive | 2014

PRECODING APPARATUS FOR PILOT CONTAMINATION

Alexei Ashikhmin; Thomas L. Marzetta


international symposium on information theory | 2018

Spatially-Stationary Propagating Random Field Model for Massive MIMO Small-Scale Fading

Thomas L. Marzetta


IEEE Transactions on Wireless Communications | 2018

Joint Unicast and Multi-Group Multicast Transmission in Massive MIMO Systems

Meysam Sadeghi; Emil Björnson; Erik G. Larsson; Chau Yuen; Thomas L. Marzetta


IEEE Transactions on Wireless Communications | 2018

Max–Min Fair Transmit Precoding for Multi-Group Multicasting in Massive MIMO

Meysam Sadeghi; Emil Björnson; Erik G. Larsson; Chau Yuen; Thomas L. Marzetta


asilomar conference on signals, systems and computers | 2017

Cell-free massive MIMO systems utilizing multi-antenna access points

Ahmad A. I. Ibrahim; Alexei Ashikhmin; Thomas L. Marzetta; David J. Love


Archive | 2017

sistema de transmissão mimo com estimativa e pré-codificação de canal descentralizadas

Alexei Ashikhmin; Thomas L. Marzetta


Archive | 2017

metodo de alocação de sinal piloto e aparelho para sistemas sem fio de usuário múltiplo

Alexei Ashikhmin; Thomas L. Marzetta


IEEE Transactions on Signal Processing | 2017

Channel Training for Analog FDD Repeaters: Optimal Estimators and Cramér–Rao Bounds

Stefan Wesemann; Thomas L. Marzetta

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