The recent paradigm shift towards the transmission of large numbers of mutually interfering
information streams, as in the case of aggressive spatial multiplexing, combined with …

This work introduces MultiSphere, a method to massively parallelize the tree search of large
sphere decoders in a nearly-independent manner, without compromising their maximum …

The development of high performance, low computational complexity detection algorithms is
a key challenge for real-time multiple-input multiple-output (MIMO) communication system …

Sphere decoding (SD) allows the high-dimensional MIMO maximum likelihood detection
problem to be solved with significantly lower complexity than other methods. The SD …

The sphere decoding algorithm is widely used for maximum likelihood (ML) detection in
multiple-input multiple-output (MIMO) systems, wherein the K-best sphere decoding …

The sphere decoding algorithm allows to implement the detection stage in multiple-input
multiple-output communication systems with maximum likelihood error rate performance …

The sphere decoding algorithm finds applications in multi-input multi-output (MIMO)
decoding, because it achieves near maximum likelihood (ML) detection performance with …

Massive MIMO systems are seen by many researchers as a paramount technology toward
next generation networks. This technology consists of hundreds of antennas that are …

Sphere Decoding (SD) is a highly effective detection technique for Multiple-Input Multiple-
Output (MIMO) wireless communications receivers, offering quasi-optimal accuracy with …

Sphere Decoding (SD) algorithms have been shown to provide maximum likelihood (ML)
detection over Gaussian multiple input-multiple output (MIMO) channels with lower …