The division of computer engineering at Linköping’s university is currentlydeveloping an innovative parallel DSP processor architecture called ePUMA. Onepossible future purpose of the ePUMA that has been thought of is to implement itin base stations for mobile communication. In order to investigate the performanceand potential of the ePUMA as a processing unit in base stations, a model of theLTE physical layer uplink receiving chain has been simulated in Matlab and thenpartially mapped onto the ePUMA processor.The project work included research and understanding of the LTE standard andsimulating the uplink processing chain in Matlab for a transmission bandwidth of5 MHz. Major tasks of the DSP implementation included the development of a300-point FFT algorithm and a channel equalization algorithm for the SIMD unitsof the ePUMA platform. This thesis provides the reader with an introduction tothe LTE standard as well as an introduction to the ePUMA processor. Furthermore,it can serve as a guidance to develop mixed point radix FFTs in general orthe 300 point FFT in specific and can help with a basic understanding of channelequalization. The work of the thesis included the whole developing chain from understandingthe algorithms, simplifying and mapping them onto a DSP platform,and testing and verification of the results.

MU-MIMO theory predicts manyfold capacity gains by leveraging many antennas (e.g. M >> 10) on wireless base stations to serve many users simultaneously through multi-user beamforming (MUBF). However, realizing such a large-scale design is nontrivial, and has yet to be achieved in the real world. We present the design, realization, and evaluation of Argos, the first reported large-scale base station that is capable of serving many (e.g., 10s of) terminals simultaneously through MUBF. Designed with extreme flexibility and scalability in mind, Argos exploits hierarchical and modular design principles, properly partitions baseband processing, and holistically considers real-time requirements of MUBF. To achieve unprecedented scalability, we devise a novel, completely distributed, beamforming technique, as well as an internal calibration procedure to enable implicit beamforming across large arrays. We implement a prototype with 64 antennas, and demonstrate that it can achieve up to 6.7 fold capacity gains while using a mere 1/64th the transmission power.