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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import gym
from gym import spaces
import numpy as np
class AntiJamEnv(gym.Env):
def __init__(self, jammer_type, channel_switching_cost):
super(AntiJamEnv, self).__init__()
self.observation = None
self.jammer_frequency = None
self.jammer_mode = None
self.current_channel = None
self.num_channels = 8
self.channel_bandwidth = 20 # MHz
self.frequency_range = [5180, 5320] # MHz
self.frequency_lists = range(5180, 5340, 20) # MHz
self.observation_space = spaces.Box(low=-30, high=40, shape=(self.num_channels,), dtype=np.float32)
self.action_space = spaces.Discrete(self.num_channels)
self.jammer_type = jammer_type
self.jammer_modes = ['constant', 'random', 'sweeping']
self.csc = channel_switching_cost
self._max_episode_steps = None
def reset(self):
self.current_channel = np.random.randint(self.num_channels)
if self.jammer_type == 'dynamic':
self.jammer_mode = np.random.choice(self.jammer_modes)
else:
self.jammer_mode = self.jammer_type
self.jammer_frequency = self.frequency_lists[self.current_channel]
self.observation = np.array([self._get_received_power(i) for i in range(self.num_channels)])
return self.observation
def step(self, action):
assert self.action_space.contains(action), "Invalid action"
received_power = self._get_received_power(action)
if received_power >= 0:
reward = 0.0
else:
reward = 1.0
if self.current_channel != action:
reward -= self.csc # Channel switching cost
self.current_channel = action
if self.jammer_mode == 'random':
self.jammer_frequency = np.random.uniform(self.frequency_range[0], self.frequency_range[1])
elif self.jammer_mode == 'sweeping':
self.jammer_frequency += self.channel_bandwidth
if self.jammer_frequency > self.frequency_range[1]:
self.jammer_frequency = self.frequency_range[0]
self.observation = np.array([self._get_received_power(i) for i in range(self.num_channels)])
return self.observation, reward, False, {}
def _get_received_power(self, channel_idx):
# Simulate received jamming power using normal distribution
jammed_power = np.random.normal(loc=30, scale=5)
adjacent_power = np.random.normal(loc=13, scale=3)
far_away_power = np.random.normal(loc=-7, scale=1)
if channel_idx == self.current_channel:
return jammed_power
elif abs(channel_idx - self.current_channel) == 1:
return adjacent_power
else:
return far_away_power
def render(self, mode='human'):
pass
def close(self):
pass |