Matlab code for the jammer without channel sensing in the paper "Robust remote estimation over the collision channel in the presence of an intelligent jammer"
- OptimalJammingProbability.m: Optimal jamming probability for the jammer without channel sensing beta*. Here, c=1, d=1, and X ~ N(0,1).
- OptimalJammingProbability_VS_d.m: Optimal jamming probability for the jammer without channel sensing beta* as a function of d. Here, c=1, and X ~ N(0,1).
- OptimalJammingProbability_VS_var.m: Optimal jamming probabilities beta* as a function of \sigma^2. Here, c=1, d=1 and X ~ N(0,sigma^2).
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OptimalJammingProbability_VS_cd.m: Optimal jamming probability for the jammer without channel sensing beta*as a function of
$c$ and$d$ for Fig. 2. Here, X ~ N(0,1).
Matlab code for the reactive jammer in the paper "Robust remote estimation over the collision channel in the presence of an intelligent jammer"
- Main_approximate_FNE.m: PGA-CCP algorithm for Table I.
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Optimalalphabeta_VS_d.m: Optimal jamming probabilities alpha* and beta* as a function of
$d$ . Here, c=1, and X ~ N(0,1). -
Optimalalphabeta_VS_var: Optimal jamming probabilities alpha* and beta* as a function of
$\sigma^2$ for Fig. 4. Here, c=1, d=1 and X ~ N(0,sigma^2). - PGA_CCP_Algorithm: Convergence of PGA-CCP for Fig. 6
- GDA_Algorithm.m: Convergence of GDA for Fig. 6
- FirstNashEqulibiumChecker.m: Check whether approximate First Nash Equilibrium is satisfied
- grad_PGA.m Gradients for PGA
- grad_CCP.m: Gradients for CCP
- grad_GD.m: Gradients for GD