# A New Generation of Fast and Low-Memory Smart Digital/Geometrical Beamforming MIMO Antenna
## 1 Introduction  
The emerging 6G and beyond wireless networks will be equipped with accurate user tracking capability using dynamically steered, highly focused radio beams. This will enable enhanced location-based services in addition to space division multiplexing to improve the capacity. These sharply pointed beams will also effectively combat interference in highly crowded heterogeneous environments and efficiently exploit the additional capacity of millimeter wave (mmWave) bands [1, 2]. Effective MIMO antennas are required to realize these advanced location- and movement-aware future networks. Such an effective, fast, and low-memory MIMO antenna technique is presented in this paper. It is well known that MIMO systems use multiple antennas at both the transmitter and receiver to divide and conquer the hostile wireless channel. This can help reduce interference and improve signal quality [3, 4]. The MIMO technique exploits multipath propagation, since signals received from multiple paths are intelligently combined at thereceiver to reconstruct the original signal [5]. Minimizing interference is achieved by creating nulls in the beam (that is, radiation nulls). In the directions of the beam nulls, the signal is weak or non-existent. However, the most significant advantage of the MIMO is its beamforming and beamsteering capabilities. Hence, MIMO offers a significant increase in channel capacity without additional bandwidth and it reduces power consumption. The MIMO technology is a key component of many modern wireless communication standards, such as 802.11n and 802.11 ac Wi-Fi, and 5G and 6G cellular networks [2; 4; 6]. With the vast development of MIMO technology, smart MIMO antennas are being intensely researched to improve performance with low hardware and software complexity. Smart MIMO antennas use advanced signal processing techniques for performance improvement. They have the ability to adapt to changing conditions in the environment, such as the level of interference, in addition to providing user tracking. A smart MIMO antenna can optimize its performance in real time and improve communication speed, capacity, and reliability [7]. Smart antennas are customarily categorized as either switched beam or adaptive array systems based on their operational modes. Switched beam antennas use a finite number of predefined, static, fixed radiation patterns and switch among them as needed. They do not usually use real-time feedback. On the other hand, in an adaptive array antenna system, an infinite number of patterns can be obtained, and these beams can be continuously steered by rapidly adjusting the signal phase angles of each antenna element. For instance, it can dynamically track different types of users, adapt to changing channel conditions, minimize interference, and maximize signal reception by adjusting its parameters in real time [3; 8]. Smart antenna technology can spatially track mobile devices by adapting its radiation pattern to optimize both transmission and reception to/from each user's device [3]. Single beamforming and beamsteering can especially assist in avoiding problematic side lobe radiations. In order to obtain effective and rotatable beams, signals from multiple elements of a nonlinear antenna array can be appropriately combined. This is achieved by organizing phase delays in the antenna array elements in specified patterns in space [7; 9; 10]. The use of advanced signal processing techniques and artificial intelligence algorithms allows for the optimization of the power and direction of the signal to/from each user, which in turn reduces interference and noise, thereby increasing the communication quality [11]. In this paper, a smart MIMO antenna system is proposed based on the antenna architectures described in [3]. The proposed smart MIMO antenna has the ability to maximize its directional gain by optimizing the phase delay factors of its elements. The validation of this proposed antenna architecture is achieved in a three-dimensional space using Wolfram Mathematica(r) software.