In this paper, a deep learning (DL)-based sphere decoding algorithm is proposed, where the
radius of the decoding hypersphere is learned by a deep neural network (DNN). The …

A modified sphere decoding (SD) scheme is proposed for multiple-input multiple-output
(MIMO) communication systems in this paper. The contribution of the paper includes the …

Although the sphere decoder (SD) is a powerful detector for multiple-input multiple-output
(MIMO) systems, it has become computationally prohibitive in massive MIMO systems …

In this paper, we propose a deep learning based sphere decoding (SD) scheme to reduce
the detection complexity for the multiple-input multiple-output (MIMO) communication …

In this letter, we propose a reordering of the channel representation for Sphere Decoding
(SD) where the real and imaginary parts of each jointly detected symbol are decoded …

A new generalized sphere decoder (GSD), called a double-layer sphere decoder (DLSD), is
proposed for under-determined MIMO systems with fewer receive antennas N than transmit …

For underdetermined linear systems, original sphere decoding (SD) algorithms fail due to
zero diagonal elements in the upper-triangular matrix of the QR or Cholesky factorization of …

This paper presents a novel pre-processing stage that offers significant improvement in the
computational efficiency of sphere decoding by imposing a geometrically-inspired ordering …

We start by identifying a relatively efficient version of sphere decoding algorithm (SDA) that
performs exact maximum-likelihood (ML) decoding. We develop novel algorithms based on …

Sphere decoders (SDs) are known to provide near maximum-likelihood performance in
multiple-input multiple-output systems. But their ability to provide good error performance …