8.6.3 Spatial Multiplexing (MIMO)

Spatial multiplexing extends the concept of beamforming by exploiting the structure of the propagation channel itself to support multiple independent data streams over the same time–frequency resources. This approach is commonly described as multiple-input multiple-output (MIMO) transmission.

Consider a transmitter equipped with N_t antennas and a receiver equipped with N_r antennas. The propagation channel between them can be represented by a matrix that relates transmitted signals to received signals. If the channel matrix has rank r, where r ≤ min(N_t, N_r), then up to r independent spatial data streams may, in principle, be transmitted simultaneously.

Unlike classical beamforming, which focuses energy in a single direction to improve signal-to-interference ratio, spatial multiplexing uses multiple spatial modes of the channel to carry parallel streams. The receiver separates these streams using signal processing techniques that exploit differences in spatial signatures across the antenna array.

The achievable capacity of a MIMO system increases approximately linearly with the number of independent spatial streams, provided that channel conditions support sufficient spatial diversity. In rich scattering environments, where signals arrive via multiple independent paths, the channel matrix is more likely to have high rank, enabling greater multiplexing gain. In highly line-of-sight environments with limited scattering, spatial modes may be strongly correlated, reducing achievable multiplexing.

Spatial multiplexing differs from spatial reuse in an important way. In spatial reuse, different users are separated by direction, and each user occupies a distinct beam. In spatial multiplexing, multiple streams may be directed toward the same user or set of users and separated through spatial processing at the receiver. Both approaches exploit the spatial dimension, but multiplexing increases per-link throughput while reuse increases multiuser capacity.

Practical MIMO systems require accurate channel estimation, calibration among antenna elements, and sophisticated detection algorithms. As antenna counts increase, processing complexity and hardware demands grow correspondingly. Nevertheless, spatial multiplexing has become central to modern broadband wireless and satellite systems because it provides a means of increasing capacity without requiring additional bandwidth.

Spatial multiplexing therefore represents the most advanced form of deterministic spatial separation. Together with geometric reuse and beamforming, it completes the spatial-division framework.