## 3 Emerging and State-of-the-Art Technologies
### Multiple-Input Multiple-Output (MIMO)  
In recent years, the term _MIMO_ has dominated the scientific discourse, promising to address the inherent losses of mmWave communication. However, strictly speaking, this is a widespread misconception, as it is the directional antenna beams that mitigate mmWave losses through their high gain, not merely the multiple ports of the antenna array. Among its key advantages, massive MIMO's ability to significantly enhance channel capacity stands out [78]. The term \"massive\" refers to the inclusion of a large number of antenna elements in the system, often exceeding hundreds and potentially reaching thousands [79]. This extensive array of elements forms the foundation for robust adaptive techniques aimed at mitigating noise and boosting received signal power. Furthermore, beamforming has become an integral component of MIMO systems, improving system gain and overall performance. Currently, MIMO systems typically employ configurations such as sub-arrays with \(4\times 4\) antenna elements, particularly in the sub-\(6\) GHz range, where physical size and system complexity remain limiting factors [80]. MIMO technology leverages multipath communication, exploiting the diverse propagation paths of RF signals to increase channel capacity. This phenomenon is more pronounced in the lower microwave frequency bands (e.g., sub-\(7\) GHz) than at mmWave bands. Notably, multipath dominates at sub-\(7\) GHz, while direct line-of-sight (LOS) is the principal link at mmWave frequencies. MIMO increases capacity by processing distinct signals through transceiver modules, transmitting them from individual elements or subarrays within an antenna array, and subsequently applying post-processing at the receiver to reconstruct the transmitted data. The efficiency of this process is heavily dependent on the algorithms that encode and decode signals based on the channel's characteristics [78]. Consequently, a significant body of research focuses on developing advanced algorithms and adaptive techniques to optimize MIMO system performance. One critical challenge is the requirement for real-time processing to accommodate the dynamic nature of the wireless environment. This necessitates continuous monitoring of the channel's characteristics and frequent updates to the channel matrix for each frequency component to ensure seamless operation. Massive MIMO's capacity to adapt to changing environments and enhance communication reliability makes it an indispensable technology for next-generation wireless networks. However, appropriate topologies combining MIMO and beamforming must be exploited to address the challenges of mmWave frequencies effectively. A commonly cited advantage supporting the development of massive MIMO systems or massive element arrays at mmWave frequencies is the relative ease of fabricating antenna arrays with hundreds or even thousands of elements within a compact space, enabled by the short wavelengths at these frequencies [79; 81; 82; 83; 84; 85; 86]. However, this advantage is counterbalanced by a critical limitation. Specifically, the primary benefit of MIMO, its ability to exploit multipath propagation, is significantly diminished at mmWave frequencies due to increased free space path loss and substantial attenuation from atmospheric gases and water vapor (Figure 2). To compensate for these losses, antenna systems must achieve considerably higher gain, as the available power is inherently constrained at these frequencies. This requirement necessitates the use of beamforming techniques, which focus energy along a single LOS propagation path. While effective in overcoming propagation challenges, beamforming largely eliminates the ability to capitalize on multipath diversity, which is a key advantage of MIMO technology at lower frequencies. Consequently, at mmWave frequencies, the potential benefits of massive MIMO in harnessing multipath propagation are significantly diminished.