  In conventional communication systems, any interference between two
communicating points is regarded as unwanted noise since it distorts the
received signals. On the other hand, allowing simultaneous transmission and
intentionally accepting the interference of signals and even benefiting from it
have been considered for a range of wireless applications. As prominent
examples, non-orthogonal multiple access (NOMA), joint source-channel coding,
and the computation codes are designed to exploit this scenario. They also
inspired many other fundamental works from network coding to consensus
algorithms. Especially, federated learning is an emerging technology that can
be applied to distributed machine learning networks by allowing simultaneous
transmission. Although various simultaneous transmission applications exist
independently in the literature, their main contributions are all based on the
same principle; the superposition property. In this survey, we aim to emphasize
the connections between these studies and provide a guide for the readers on
the wireless communication techniques that benefit from the superposition of
signals. We classify the existing literature depending on their purpose and
application area and present their contributions. The survey shows that
simultaneous transmission can bring scalability, security, low-latency,
low-complexity and energy efficiency for certain distributed wireless scenarios
which are inevitable with the emerging Internet of things (IoT) applications.
