In this paper, we address the problem of signal detection in multiple-input multiple-output
(MIMO) orthogonal frequency division multiplexing (OFDM) system by using auto-encoder …

This paper proposes a deep learning (DL) based method for signal detection in multiple-
input multiple-output orthogonal frequency division multiplexing with index modulation …

Requirements for higher data rates and lower power consumption set new challenges for
implementation of multiple-input multiple-output orthogonal frequency division multiplexing …

Although the QR decomposition M algorithm (QRD-M) detection reduces the complexity and
achieves near-optimal detection performance, its complexity is still very high. In the …

Extreme learning machine (ELM) is commonly adopted and best known for its extremely fast
learning capability and notable performance. In this paper, a multiple split-complex ELM …

In this paper, we consider a real-time deep learning-based symbol detection approach for
MIMO-OFDM systems. To exploit the temporal correlation of the wireless channel and the …

Deep learning (DL) is playing an increasingly important role in the design of next-generation
communication systems. In this paper, we apply DL algorithms to enhance signal detection …

MEMO-OFDM system has been currently recognized as one of the most competitive
programs for 4G mobile wireless systems. MIMO-OFDM system can compensate for the …

In this paper, a novel efficient algorithm for MIMO detection in MIMO-OFDM systems has
been proposed. This paper also shows that the complexity can be greatly reduced by …

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM), a
fundamental transmission scheme, promises high throughput and robustness against …