No abstract

No abstract

Many-antenna base stations promise manyfold spectral capacity increases in theory. However, our recent experimental work has shown a significant performance gap between the traditional MU-MIMO linear precoding method, zeroforcing, and the method proposed for many-antenna base stations, conjugate. Thus, a critical question in the field of many-antenna base stations is: Under what scenarios, if any, does conjugate precoding outperform zero-forcing in real systems?Towards answering this question, we leverage our experience in building many-antenna base stations to derive a model for the performance of linear precoders in real-world systems. We isolate the primary factors which discrepantly affect these linear precoders, then capture their complex interactions in an analytical model. By combining our realworld capacity results with this analytical model, we find new insight in to the tradeoffs between conjugate and zeroforcing precoding. Our results suggest that conjugate will outperform zero-forcing when there are many simultaneous users, the users have high mobility, or the implementation employs less-capable hardware. We find that our model is not only useful for guiding the hardware design of base stations, but can also facilitate dynamically switching to the optimal linear precoding algorithm in realtime, through adaptive precoding.

No abstract

No abstract