# Technology Trends for Massive MIMO towards 6G
## 3 Localization and Sensing Using Metasurface-Enabled Massive MIMO  
In the forthcoming 6G era, wireless localization and sensing functionalities will be integrated into a myriad of applications, including navigation, transportation, and healthcare [14]. Consequently, there is a strong demand for services that deliver fine-resolution sensing and high localization accuracy. Massive MIMO emerges as a promising solution to  
Figure 1: Transmission model of an intelligent surface element. this requirement, as it can narrow the beam width with a larger antenna array, resulting in high spatial resolution. However, the wireless environments in these systems are becoming complicated, for example, line-of-sight (LoS) links might be blocked by buildings or objects, degrading the accuracy of sensing and localization. Fortunately, the development of the metasurface makes it a promising solution to achieve massive MIMO, thus improving the sensing and localization accuracy by altering the propagation environment [15]. On the one hand, metasurfaces deployed in the environment can provide additional paths toward targets, extending the coverage. On the other hand, with the capability of manipulating propagation conditions, the signals from different objects or targets can be customized so that they are easier to be distinguished, as illustrated in Figure 2.  
Nevertheless, the integration of the metasurface (could be IRS, RRS, or IOS according to the use case) in a wireless sensing/localization system is not trivial, which generally brings the following challenges:  
* It will be a challenge to optimize the configurations relating to the metasurface [16]. Different from the designs of the metasurface for communication purposes, the optimizations here aim to maximize the sensing/localization performance, necessitating new designs. For example, the metric could be defined as the distance between two signal patterns (each corresponding to a configuration of the metasurface) from different targets/positions so that the receiver could recognize two targets/positions with less effort, leading to a higher accuracy. Moreover, as the number of metasurface elements could be large, it will cause a prohibitively high delay to enumerate all the configurations. Therefore, it will be important to select an appropriate number of configurations to achieve the trade-off between latency and accuracy. * The coupling of the decision function with the optimization of the metasurface makes it hard to find the optimal function. To be specific, the receiver needs a decision function to transform the received signals into the information of targets/positions. As the received signals can be adjusted by the metasurface, the selection of the decision function is also influenced by the configurations of the metasurface. Therefore, a joint optimization will be necessary to improve the performance [17]. * As the spectrum is scarce in wireless systems, it is hard to spare extra bandwidth to realize the sensing function, and thus integrated sensing and communication (ISAC) becomes a natural solution [18]. Since the metasurface has different impacts on communication and sensing functions, it should be carefully configured to achieve a win-win integration of sensing and communication performance. To be specific, the mutual interference between sensing and communication can be alleviated using the  
Figure 2: Illustration for wireless localization and sensing using metasurface-enabled massive MIMO systems. metasurface. Moreover, a performance trade-off between sensing and communication needs further investigation. * In addition to the above signal processing challenges, practical implementation is another challenge. Where to deploy the metasurface and how to determine its size should be carefully addressed, which should also take the topology of the environment into consideration. To sum up, massive MIMO technology will be expected to provide multi-functional services integrating communication, localization, and sensing.