The course covers the fundamental theory for how antenna arrays can be utilized to achieve more efficient wireless communication systems, for example, in 5G cellular networks. The focus is on physical layer aspects, including channel estimation, spectral efficiency computation, spatial signal processing, and power optimization. The course covers the fundamentals of “Massive MIMO (multiple input multiple output), point-to-point MIMO, as well as modeling of line-of-sight and fading multi-antenna channels. The course is recommended for doctoral students with an interest in wireless communications and its applications, and no previous third-cycle courses on topic are required.
P4, VT21
14 lectures, each consisting of around 45 min video to watch in advance and 90 min of examples and discussions in class.
8 tutorial sessions that require preparations and active attendance.
2 lab exercises that each is expected to take around 5 hours to solve.
4 homework sets with around 5 exercises each.
Fundamental limits: Capacity behavior as power or bandwidth increases. Examples of practical systems that are power and bandwidth limited. Orthogonal versus non-orthogonal transmission in scenarios with multiple users.
Basic multiple antenna channels: Array gain, capacity of channels with multiple antennas at one side. Modeling of multi‐antenna channel responses.
Fading channels: Rayleigh fading channels, outage capacity, diversity, channel coherence, ergodic capacity.
Point‐to‐point MIMO: Capacity of channels with multiple antennas at both sides, multiplexing gain, spatial degrees of freedom.
Uplink multi‐user MIMO: Uplink capacity, non‐linear and linear detection, channel estimation, capacity bounds in systems with many antennas.
Downlink multi‐user MIMO: Linear precoding, capacity bounds in systems with many antennas, differences and similarities between uplink and downlink.
Power control: Rate region, typical operating points, basic power allocation formulations.
Cellular networks: Engineering aspects of applying multiple antenna techniques in cellular networks, including reuse strategies, pilot contamination, and interference management.
After passing the course, the student should
Enrolled as doctoral student.
From linear algebra and calculus: Computations with matrices and vectors, determinant, eigenvalues. Computations with complex numbers.
From mathematical statistics: Stochastic variables, estimation of realizations of stochastic variables.
From elementary communication theory: Channel models, channel capacity, the entropy concept.
Lab exercises are carried out in MATLAB.
Compendium “Introduction to Multiple Antenna Communications” written by E. Björnson
T. L. Marzetta, E. G. Larsson, H. Yang, and H. Q. Ngo, Fundamentals of Massive MIMO. Cambridge University Press, 2016.
If the course is discontinued, students may request to be examined during the following two academic years.
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
The examination consists of three parts: A written exam, laboratory exercises carried out in MATLAB, and a set of homework problems that are solved individually and then actively discussed in joint tutorial sessions.
The grade on the course is Pass/fail. The requirements for passing the course is at least 2/3 correct answers on the written exam and on the homework problems, correct solutions to the laboratory exercises and a lab report of sufficient quality. Moreover, 90% attendance on the scheduled laboratory exercises and tutorials is required.
Parts of the lecture material consists of videos.
