Arbitrarily parallel turbo decoding for ultra-reliable low latency communication in 3GPP LTE

In order to meet the latency requirements of the Ultra-Reliable Low Latency Communication (URLLC) mode of the 3GPP Long Term Evolution (LTE) mobile communication standard, this paper proposes a novel turbo decoding algorithm that supports an arbitrarily-high degree of parallel processing, facilitating significantly higher processing throughputs and substantially lower processing latencies than the state-of-the-art (SOTA) LTE turbo decoder. As in conventional turbo decoding algorithms, the proposed Arbitrarily Parallel Turbo Decoder (APTD) decomposes each frame of information bits into a sequence of windows, where the bits within different windows are processed simultaneously using forward and backward recursions in a serial manner. However, in contrast to conventional turbo decoding algorithms, the APTD does not require the different windows to be composed of an identical number of bits, which allows the use of an arbitrary number of windows and hence an arbitrary degree of parallelism, when decoding information bits of an arbitrary frame length. Furthermore, conventional turbo decoding algorithms alternate between simultaneously processing the windows in the upper decoder and those in the lower decoder. By contrast, the APTD processes the odd-indexed windows in the upper decoder at the same time as the even-indexed windows in the lower decoder and alternates between this and the reversed arrangement, hence further improving the decoding throughput and latency. Furthermore, the APTD achieves a reduced hardware resource requirement by calculating the extrinsic information based only on the outputs of the forward recursions, rather than based on both the forward and backward recursions of conventional turbo decoding algorithms. We demonstrate that the proposed APTD achieves superior latency, throughput and computational efficiency than the SOTA LTE turbo decoder at all frame lengths, but particularly at the short frame lengths that are typically used in URLLC approach..