REDUCING SIGNAL PROCESSING COMPLEXITY FOR MASSIVE MIMO
One technical challenge in developing massive MIMO systems is the signal processing complexity.
As transmit and receive signals are quite lengthy, the search algorithms must be performed over many possible permutations of symbols.
In the current literature, massive MIMO research is often treated as a detection problem based on a search motivated by the well-known ML criterion.
The existing detection algorithms assume that the channel has been perfectly estimated, which appears to be an unreasonable assumption given the size of the channel matrix and thus amount of channels to be tracked.
A possible solution to this problem is to apply the SM concept to massive MIMO systems. In this case, the spatial signature of each antenna needs to be different from the point of view of the receiver because data is encoded into the choice
of transmit antenna active in the transmit array.
It is therefore possible that channel estimation does not need to be exact but rather be merely sufficient to distinguish each transmit antenna.
This may be a reasonable prospect, especially if the receive array is large, in which case each transmit antenna would have a quite detailed and thus distinct spatial signature.