Mohammad Attari defends his thesis: Application Specific Instruction-set Processors for Massive MIMO Systems

This is an undeniable fact now that wireless systems pervade all aspects of our lives. These systems are evolving at a rapid clip, connecting more people and devices every single day that goes by. This growth is further fueled by the users’ insatiable appetite for more traffic, be it for online gaming, watching high-fidelity video, downloading huge files, live- streaming and many more uses. With the advent of internet of things (IoT), which brings a countless number devices and sensors into the picture, this growth turns into an unstoppable force.
Catering to the connectivity and data rate demands that these applications and devices place on the wireless communi- cations infrastructure is not a trivial issue. As the old 4G systems are approaching, or rather have already surpassed, their limits, the new kids on the block are 5G and what comes beyond. These systems are developed specifically to bump up the data rates, provide better coverage, and increase the overall energy and spectral efficiencies. In order to facilitate this, a number of key technologies have proven themselves instrumental. One such technology is the massive multiple-input multiple-output (MIMO), which scales up the number of antennas available in the base station (BS) to the hundreds, in order to add space as yet another degree of freedom to the system, creating the holy trinity of time-frequency-space. This is crucial, considering the fact that frequency resources are limited, very expensive, and already overcrowded. This idea can be, and is being, pushed even further by employing thousands of antennas in systems such as large intelligent surfaces (LISs).
But it is not all moonlight and roses, as one might think. Incorporating these many antennas in the system puts a huge burden on data processing and data marshaling subsystems. A centralized approach does not carry the day here, and distributing the processing is not a piece of cake either. That is what this thesis concerns itself with, i.e., how to develop processors that are up to par with the requirements of above-mentioned systems in terms of performance and energy efficiency, yet are malleable enough to adapt to the vagaries of technological evolution. To this end, processor designs have been proposed here that utilize application-specific instruction set processors (ASIPs) as the firm ground to build the system upon, which are wedded to customized accelerators where more specialized units are deemed more appropriate to tackle the case at hand.
 

Link to thesis i LU Research Portal:

https://portal.research.lu.se/sv/publications/application-specific-instruction-set-processors-for-massive-mimo-

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