proposed to reduce the complexity of the SMX–ML algorithm while retaining a near optimum performance [@vb9901; @dcb0001]. The SD reduces the complexity of the ML decoder by limiting the number of possible combinations. Only those combinations that lie within a sphere centred at the received signal are considered. However, even though SMX–SD offers a large reduction in complexity compared to SMX–ML, it still has a high complexity which increases with the increase of the number of transmit antennas.

2.  Hardware complexity: In SMX the number of radio frequency (RF) chains is equal to the number of transmit antennas. From [@mw0403], RF chains are circuits that do not follow Moore’s law in progressive improvement. Therefore, increasing the number of transmit antennas and consequently the number of RF chains increases significantly the cost of real system implementation [@ssrhg1201].

3.  Energy consumption: RF chains contain Power Amplifiers (PAs) which are responsible for $50$–$80\%$ of the total power consumption in the transmitter [@czbfkgav1011]. Therefore, increasing the number of RF chains results in a decrease in the energy efficiency [@ssrhg1201].

Thus, SMX may not always be feasible and a more energy efficient and low complexity solution should be considered.

Spatial Modulation (SM) is a transmission 