Decoding and Equalization with Analog Non‐linear Networks

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Abstract
Using analog, non‐linear and highly parallel networks, we attempt to perform decoding of block and convolutional codes, equalization of certain frequency‐selective channels, decoding of multi‐level coded modulation and reconstruction of coded PCM signals. This is in contrast to common practice where these tasks are performed by sequentially operating processors. Our advantage is that we operate fully on soft values for input and output, similar to what is done in 'turbo' decoding. However, we do not have explicit iterations because the networks float freely in continuous time. The decoder has almost no latency in time because we are only restricted by the time constants from the parasitic RC values of integrated circuits. Simulation results for several simple examples are shown which, in some cases, achieve the performance of a conventional MAP detector. For more complicated codes we indicate promising solutions with more complex analog networks based on the simple ones. Furthermore, we discuss the principles of the analog VLSI implementation of these networks.

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