文件列表:

checkHexagonal.m (1468, 2017-10-28)
computeEnvironment.m (23756, 2017-10-28)
simulationAllFiguresExcept7.m (26254, 2017-10-28)
simulationFigure7.m (18372, 2017-10-28)

Massive MIMO for Maximal Spectral Efficiency ================== This is a code package is related to the following scientific article: Emil Bjornson, Erik G. Larsson, Merouane Debbah, "[Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated?](http://arxiv.org/pdf/1412.7102)," IEEE Transactions on Wireless Communications, vol. 15, no. 2, pp. 1293-1308, February 2016. The package contains a simulation environment, based on Matlab, that reproduces all the numerical results and figures in the article. *We encourage you to also perform reproducible research!* ## Abstract of Article Massive MIMO is a promising technique to increase the spectral efficiency (SE) of cellular networks, by deploying antenna arrays with hundreds or thousands of active elements at the base stations and performing coherent transceiver processing. A common rule-of-thumb is that these systems should have an order of magnitude more antennas, M, than scheduled users, K, because the users' channels are likely to be near-orthogonal when M/K > 10. However, it has not been proved that this rule-of-thumb actually maximizes the SE. In this paper, we analyze how the optimal number of scheduled users, K^\star, depends on M and other system parameters. To this end, new SE expressions are derived to enable efficient system-level analysis with power control, arbitrary pilot reuse, and random user locations. The value of K^\star in the large-M regime is derived in closed form, while simulations are used to show what happens at finite M, in different interference scenarios, with different pilot reuse factors, and for different processing schemes. Up to half the coherence block should be dedicated to pilots and the optimal M/K is less than 10 in many cases of practical relevance. Interestingly, K* depends strongly on the processing scheme and hence it is unfair to compare different schemes using the same K. ## Content of Code Package The article contains 11 simulation figures, numbered from 4 to 14. These are generated by the Matlab scripts simulationAllFiguresExcept7.m and simulationFigure7.m. The package contains two additional Matlab functions which are called by the main scripts: computeEnvironment.m and checkHexagonal.m. See each file for further documentation. ## Acknowledgements This research has received funding from the EU 7th Framework Programme under GA no ICT-619086 (MAMMOET). This research has been supported by ELLIIT, the International Postdoc Grant 2012-228 from the Swedish Research Council and the ERC Starting Grant 305123 MORE (Advanced Mathematical Tools for Complex Network Engineering). ## License and Referencing This code package is licensed under the GPLv2 license. If you in any way use this code for research that results in publications, please cite our original article listed above.

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