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 …

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 …

In multiple‐input multiple‐output (MIMO) systems, sphere decoding (SD) can achieve a
performance equivalent to a full‐search maximum likelihood decoding, with reduced …

In this paper, we propose a novel learning-aided sphere decoding (SD) scheme for large
multiple-input-multiple-output systems, namely, deep path prediction-based sphere …

It is well known that although the conventional sphere decoder (SD) achieves optimal
maximum likelihood (ML) performance at a reduced complexity compared to the naive ML …

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 …

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 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 …

In this letter, we propose an extension of the probabilistic tree pruning sphere decoding
(PTP-SD) algorithm that provides further improvement of the computational complexity with …