Multimode fibers (MMFs) are limited in data rate capabilities owing to modal dispersion. However, their large core diameter simplifies alignment and packaging, and makes them attractive for short and medium length links. Recent research has shown that the use of signal processing and techniques such as multiple-input multiple-output (MIMO) can greatly improve the data rate capabilities of multimode fibers. In this paper, we review recent experimental work using MIMO and signal processing for multimode fibers, and the improvements in data rates achievable with these techniques. We then present models to design as well as simulate the performance benefits obtainable with arrays of lasers and detectors in conjunction with MIMO, using channel capacity as the metric to optimize. We also discuss some aspects related to complexity of the algorithms needed for signal processing and discuss techniques for low complexity implementation.
This paper considers the classic non-causal state information problem in channel coding where non-causal channel state knowledge at the transmitter, which is also called the Gel'fand Pinsker problem. This paper determines Lagrangian dual expression for this problem, illustrating that Costa's dirty paper coding result can be replicated using the dual-problem methodology.