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Simulation of Massive MIMO System Performance



Multiple-antenna (MIMO) technology is becoming mature for wireless communications and has been incorporated into wireless broadband standards like LTE and Wi-Fi. Basically, the more antennas the transmitter/receiver is equipped with, the more the possible signal paths and the better the performance in terms of data rate and link reliability. The price to pay is increased complexity of the hardware (number of RF amplifier frontends) and the complexity and energy consumption of the signal processing at both ends.

Massive MIMO makes a clean break with current practice through the use of a very large number of service antennas (e.g., hundreds or thousands) that are operated fully coherently and adaptively. Extra antennas help by focusing the transmission and reception of signal energy into ever-smaller regions of space. This brings huge improvements in throughput and energy efficiency, in particularly when combined with simultaneous scheduling of a large number of user terminals (tens or hundreds). Other benefits of massive MIMO include the extensive use of inexpensive low-power components, reduced latency, simplification of the media access control (MAC) layer, and robustness to interference and intentional jamming.

Problem statement

The task consists of implementing a system simulation framework, incorporating the effects of power control, pilot reuse, channel estimation and mobility. The technical/scientific goal of the task is to evaluate the system performance advantage of massive MIMO, relative to an LTE-like baseline system.


The student needs a strong background in mathematics, communication systems and good skills in Matlab or C++ programming.


[1] E. G. Larsson, F. Tufvesson, O. Edfors, and T. L. Marzetta, Massive MIMO for Next Generation Wireless Systems, IEEE Commun. Mag., vol. 52, no. 2, pp. 186-195, Feb. 2014.
[2] F. Rusek, D. Persson, B. K. Lau, E. G. Larsson, T. L. Marzetta, O. Edfors, and F. Tufvesson, Scaling up MIMO: Opportunities and Challenges with Very Large Arrays, IEEE Signal Proces. Mag., vol. 30, no. 1, pp. 40-46, Jan. 2013.

Page responsible: Danyo Danev
Last updated: 2014 10 09   16:35