Can I create a layer with multiple rnn cell ? [question about a paper]
Not exactly familiar with this model architecture but, I don't think it works the way you described it.
From a quick skim, a simplified overview of the model may be

data input: $X$ multiple time series
RNN: pass each time series $x$ through a recurrent neural network and grab its hidden state
Joint embedding: Concat hidden states from each $x$ series into an embedding with $X$ channels
Convnet


But I didn't see there is a way to create multiple rnn cells in same layer , do I misunderstand?? If not , could you please give me a guide or an example ?

Essentially, any rnn will have a number of cells equal to the number of time steps. As an example, in NLP that number of cells would be equal to the number of words in a sentence, where each sentence in your trainset must have the same length.
I suggest you familiarise yourself with sequence models to better understand the concept of this paper.