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class FooEnv(gym.Env): metadata = {'render.modes': ['human']} def __init__(self, readDistance = True, filename="Data_for_Train.csv", MaxStep = 81): globe._init() # the location of UAV-RIS globe.set_value('L_U

The above code defines a custom environment called “FooEnv” that inherits from the OpenAI Gym Env class. The environment is initialized with several global parameters related to the communication network between an unmanned aerial vehicle (UAV) equipped with a reconfigurable intelligent surface (RIS) and a ground station.

The constructor of the environment takes several arguments, including readDistance, filename, and MaxStep. If readDistance is set to True, the environment reads in distance data from a CSV file specified by filename. MaxStep specifies the maximum number of time steps for which the environment will run.

The globe module is used to store global variables that are used throughout the environment’s methods. These include the location of the UAV-RIS and AP/BS, CSI parameters such as bandwidth and noise power spectrum density, and RIS-related parameters such as energy harvesting efficiency and additional attenuation factor.

The action space for this environment is defined as a single float value between 0 and 1 using a Box space. The observation space consists of two float values between 0 and 60 also using a Box space.

Overall, this code defines an environment for simulating communication between a UAV-RIS system and a ground station while taking into account various environmental factors such as path loss, noise, and signal interference.

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