## 2 Related Work  
This section extensively presents evaluation studies of IEEE 802.11 ad communication performance to discuss a simple and inexpensive IEEE 802.11 ad measurement for non-specialists. We also describe the differences between this study and others throughout this survey. Many existing works provide analytical/simulation models and empirical results on mmWave and IEEE 802.11 ad communication performance. Reference [8] proposed an analytical/simulation model to analyze the dependencies of the contention period and the number of sectors on the MAC delay and throughput. In [9], 6G wireless channel measurements, characteristics, and models were comprehensively reviewed for their trends and challenges. Simulation models have also been developed to evaluate the protocol performance with parameters in different scenarios [10; 11; 12; 13; 14]. References [10; 11] implemented the IEEE 802.11 ad model for ns-3 [15], which is known as one of the dominant network simulators. References [12; 13; 14] proposed an integrated simulation framework to evaluate the communication performance of UAVs in the mmWave environment. Simulators are very helpful and cost-effective for investigating communication and protocol performances in various scenarios. Such analytical/simulation models are indispensable for understanding the general characteristics at the R&D stage. Empirical studies based on real environments are also crucial in the diffusion and operational phases. The subsequent studies provided practical evaluations for various characteristic aspects. References [16; 17; 18] focus on the characteristics of a wireless link, and reference [19] attempts to understand the interference characteristics and effectiveness of interference mitigation techniques using 802.11 ad commercial off-the-shelf (COTS) devices. However, since special equipment such as a vector network analyzer and a software radio system is required, a high level of expertise and trained experience are necessary. References [20; 21; 22; 23; 24] target the communication performance, i.e., throughput, with _ipperf3_[25]. Furthermore, the measurement studies in [26; 27; 28; 29; 30; 31] investigated communication performance in various fields. In [26], the authors studied the actual impact of consumer-grade hardware in real environments. References [27; 28; 29] investigated the influence of attenuation factors, such as interference, materials, and non-LOS, on communication performance in a vehicular environment. In [30], the authors measured drone communication using mmWaves in a real environment. Reference [31] also measured communication performance and throughput, RSSI, and power consumption for IEEE 802.11 ad COTS devices in an indoor environment. In addition, these studies employed a throughput indicator with _ipperf3_. References [32; 33; 34] developed original measurement tools that could lead to a sophisticated measurement tool. In [35], RSSI was measured by a smartphone application. As described above, many studies investigated the communication performance of Wi-Fi, including IEEE 802.11 ad, in different ways, with different tools, and in various environments. On the other hand, reference [36] concluded, \"Generally none of the examined metrics on its own, can be used for accurately determining the quality of a link. However, each metric can reveal interesting behavioral aspects of the link. A potential technique that would intelligently combine some of the metrics could yield an accurate representation of the link quality\". Hence, organizing easy-to-understand metrics contributes to stable IEEE 802.11 ad networks. Table 1 summarizes the measurement tools and the performance indicators for the existing IEEE 802.11 ad measurement studies described above. Almost all studies employ _ipperf3_ to measure throughput because the indicator is directly related to an application. In addition, the metric is easy to understand, even for non-specialists.