MIMO Receivers

In course

Description

This lecture covers the system model for MIMO receivers, including maximum likelihood receiver, linear receivers (MMSE & ZF), successive cancellation receivers, performance evaluation, and tree search algorithms. It explains the task of the MIMO detector, system model for spatial multiplexing, Voronoi regions, optimum MIMO detection, graphical interpretations, and the performance of zero forcing with a static channel. The lecture also delves into linear MIMO detection, linear zero forcing detector, Voronoi regions as decision regions, maximum likelihood detection performance, and unbiased MMSE receiver. It concludes with a discussion on graphical interpretations, linear ZF detection with QR decomposition, MMSE V-BLAST, successive interference cancellation, and comparison of basic MIMO receivers with fading.

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https://mediaspace.epfl.ch/media/0_tsafqxpb

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Related lectures (41)

Related concepts (145)

Superheterodyne receiver

A superheterodyne receiver, often shortened to superhet, is a type of radio receiver that uses frequency mixing to convert a received signal to a fixed intermediate frequency (IF) which can be more conveniently processed than the original carrier frequency. It was long believed to have been invented by US engineer Edwin Armstrong, but after some controversy the earliest patent for the invention is now credited to French radio engineer and radio manufacturer Lucien Lévy. Virtually all modern radio receivers use the superheterodyne principle.

MIMO

In radio, multiple-input and multiple-output (MIMO) (ˈmaɪmoʊ,_ˈmiːmoʊ) is a method for multiplying the capacity of a radio link using multiple transmission and receiving antennas to exploit multipath propagation. MIMO has become an essential element of wireless communication standards including IEEE 802.11n (Wi-Fi 4), IEEE 802.11ac (Wi-Fi 5), HSPA+ (3G), WiMAX, and Long Term Evolution (LTE). More recently, MIMO has been applied to power-line communication for three-wire installations as part of the ITU G.

Schur decomposition

In the mathematical discipline of linear algebra, the Schur decomposition or Schur triangulation, named after Issai Schur, is a matrix decomposition. It allows one to write an arbitrary complex square matrix as unitarily equivalent to an upper triangular matrix whose diagonal elements are the eigenvalues of the original matrix. The Schur decomposition reads as follows: if A is an n × n square matrix with complex entries, then A can be expressed as where Q is a unitary matrix (so that its inverse Q−1 is also the conjugate transpose Q* of Q), and U is an upper triangular matrix, which is called a Schur form of A.

Spatial multiplexing

Spatial multiplexing or space-division multiplexing (SM, SDM or SMX) is a multiplexing technique in MIMO wireless communication, fibre-optic communication and other communications technologies used to transmit independent channels separated in space. In fibre-optic communication SDM refers to the usage of the transverse dimension of the fibre to separate the channels. Multi-core fibres are fibres designed with more than a single core.

QR decomposition

In linear algebra, a QR decomposition, also known as a QR factorization or QU factorization, is a decomposition of a matrix A into a product A = QR of an orthonormal matrix Q and an upper triangular matrix R. QR decomposition is often used to solve the linear least squares problem and is the basis for a particular eigenvalue algorithm, the QR algorithm. Any real square matrix A may be decomposed as where Q is an orthogonal matrix (its columns are orthogonal unit vectors meaning ) and R is an upper triangular matrix (also called right triangular matrix).