Massive antenna arrays can be used to meet the requirements of 5G, by exploiting different
spatial signatures of users. This same property can also be harnessed to determine the …

Channel estimation is a crucial problem for massive multiple input multiple output (MIMO)
systems to achieve the expected benefits in terms of spectrum and energy efficiencies …

For estimating the MIMO channels for both the uplink and the downlink, we used residual
deep neural network. The proposed residual deep neural network (ResNET) channel …

Millimeter wave multiple-input-multiple-output (MIMO) achieves the best performance when
reliable channel state information is used to design the beams. Most channel estimation …

In this paper, a novel tensor-based method is proposed to equalize frequency-selective
multiple-input multiple-output (FS-MIMO) channels. Since both the spatial and temporal …

In this paper, we address the problem of joint downlink (DL) and uplink (UL) channel
estimation for millimeter wave (mmWave) multiple‐input multiple‐output (MIMO) systems …

We applied residual deep neural network for high noise power region uplink channel
estimation. Proposed residual deep neural network channel estimation show more 1 dB …

Channel state information (CSI) estimation in hybrid analog-digital (HAD) millimeter-wave
(mmWave) massive MIMO systems is a challenging problem due to the high channel …

This paper considers the problem of channel estimation for millimeter wave wireless
communication channels. Many existing channel estimation approaches utilize the spatial …

Algorithmic trading and portfolio optimization have revolutionized financial markets,
leveraging advanced computational models to execute trades and manage portfolios with …