A unified framework for tree search decoding: rediscovering the sequential decoder
By Arul D. Murugan, Hesham El Gamal, Mohamed Oussama Damen, Giuseppe Caire. IEEE Transactions on Information Theory, 2005
345 citations recorded by the source corpus.
We consider receiver design for coded transmission over linear Gaussian channels. We restrict ourselves to the class of lattice codes and formulate the joint detection and decoding problem as a closest lattice point search (CLPS). Here, a tree search framework for solving the CLPS is adopted. In our framework, the CLPS algorithm is decomposed into the preprocessing and tree search stages. The role of the preprocessing stage is to expose the tree structure in a form matched to the search stage. We argue that the forward and feedback (matrix) filters of the minimum mean-square error decision feedback equalizer (MMSE-DFE) are instrumental for solving the joint detection and decoding problem in a single search stage. It is further shown that MMSE-DFE filtering allows for solving underdetermined linear systems and using lattice reduction methods to diminish complexity, at the expense of a marginal performance loss. For the search stage, we present a generic method, based on the branch and bound (BB) algorithm, and show that it encompasses all existing sphere decoders as special cases. The proposed generic algorithm further allows for an interesting classification of tree search decoders, sheds more light on the structural properties of all known sphere decoders, and inspires the design of more efficient decoders. In particular, an efficient decoding algorithm that resembles the well-known Fano sequential decoder is identified. The excellent performance-complexity tradeoff achieved by the proposed MMSE-DFE Fano decoder is established via simulation results and analytical arguments in several multiple-input multiple-output (MIMO) and intersymbol interference (ISI) scenarios.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/aab8c612823dac3142c08ebaaf692893d94b89e9
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Citations in the corpus
- Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs (2015, background): “[66] Proposed a unified framework for tree search decoding, which encompasses all existing SDs as special cases, hence unifying the depth-first search, the breadth-first search and the best-first search based on the proposed framework.”
- Fixing the Complexity of the Sphere Decoder for MIMO Detection (2008, methodology): “The solution to (2) can be obtained recursively using a depth-first constrained tree search through M levels, starting from i = M down to i = 1, where P child nodes, each one corresponding to one constellation point, originate from each parent node on the tree [15].”