Week 12 – Generalizing the MIMO algorithms to a vector basis.

As I described in my last blog post, we changed the structure of the receiver.
This week, I intensively worked on the implementation of the additionally required signal processing blocks. All in all, the blocks are finished now, but there is still a lot of testing to be done. Continue reading “Week 12 – Generalizing the MIMO algorithms to a vector basis.”

Week 08 – Channel Estimation

I implemented a MIMO channel estimator this week.

The purpose of a channel estimator is the estimation of the channel state information (CSI) which is required for many MIMO algorithms. The goals for such an estimator are a small estimation error but also a low estimation complexity and a small proportion of training data in comparison to the actual payload. Continue reading “Week 08 – Channel Estimation”

Week 07 – MIMO-OFDM

This week, I started with the last big milestone for this summer: The integration of the MIMO algorithms into an OFDM transceiver system.

In the first part of this article I want to describes the requirements and how I imagine the out coming result of this MIMO-OFDM transmitter. This includes intensive thoughts about the transceiver’s structure. After that, I want to present my detailed step-by-step plan of how I want to approach this project. Continue reading “Week 07 – MIMO-OFDM”

Week 06 – Expanding the V-BLAST scheme to MxM

I expanded the 2×2 V-BLAST zero-forcing scheme to a general MxM scheme. For a general MxM matrix, the inverse cannot be precalculated by hand as I did for the 1×1 and 2×2 scheme. The inversion of a possibly large channel matrix can quickly get a very complex problem which needs a lot of computation power, especially if it is recalculated frequently, for example each micro second when assuming a coherence time of 1μs and therefore a CSI update rate of 1MHz. Continue reading “Week 06 – Expanding the V-BLAST scheme to MxM”

Week 05 – About Inverses and Pseudo-Inverses

Last week, I implemented a V-BLAST encoder which demultiplexes a data stream into M parallel streams that are simultaneously sent through the same channel. This was a really simple task which granted us a data rate increase of factor M without the need of a complex transmitter complexity.

This week, we have to ‘clean up the mess we made’ at the receiver, meaning that we have to demultiplex the parallel data streams again by separating the M parallel symbols which are sent from one transmitting antenna, respectively, to each of the N receiving antennas. Continue reading “Week 05 – About Inverses and Pseudo-Inverses”