InformationTheory

InformationTheory.Shannon.MultipleAccess.JointTypicality

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Multiple access channel — three-way jointly typical set #

The three-way jointly typical set for a two-user MAC, following the single-user InformationTheory.Shannon.ChannelCoding.jointlyTypicalSet conventions (Cover–Thomas).

Design #

The single-user typical set InformationTheory.Shannon.typicalSet is an entropy-typicality set (empirical entropy within ε of the true entropy), not a strong / letter-typicality set. Consequently a three-way (X₁, X₂, Y)-joint-typical triple does not by itself entail any of the pairwise-typical facts (e.g. (X₂, Y)-pair-typical). The achievability error analysis needs those pairwise facts to bound the conditional-fibre masses, so macJointlyTypicalSet is defined as the intersection of all the single-axis, pairwise, and three-way typicality conditions.

This shape makes each of the three "one user uses a wrong codeword" reductions a syntactic instance of the single-user jointly-typical set under regrouping:

  • user 1 wrong: X₁ ⟂ (X₂, Y) reduces to jointlyTypicalSet μ X₁s (jointSequence X₂s Ys),
  • user 2 wrong: X₂ ⟂ (X₁, Y) reduces to jointlyTypicalSet μ X₂s (jointSequence X₁s Ys),
  • both wrong: (X₁, X₂) ⟂ Y reduces to jointlyTypicalSet μ (jointSequence X₁s X₂s) Ys.

Main definitions #

  • macJointSequence X₁s X₂s Ys — the three-way joint sequence i ω ↦ (X₁s i ω, X₂s i ω, Ys i ω).
  • macJointlyTypicalSet μ X₁s X₂s Ys n ε — the three-way jointly typical set, the intersection of the three single-axis, three pairwise, and one three-way typicality conditions.
noncomputable def

InformationTheory.Shannon.MAC.macJointSequence

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{Ω : Type u_1} {α₁ : Type u_2} {α₂ : Type u_3} {β : Type u_4} (X1s : ℕ → Ω → α₁) (X2s : ℕ → Ω → α₂) (Ys : ℕ → Ω → β) :
ℕ → Ω → α₁ × α₂ × β

The three-way joint sequence over the product alphabet α₁ × α₂ × β. Definitionally equal to jointSequence X₁s (jointSequence X₂s Ys) (right-associated nesting).

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      theorem

      InformationTheory.Shannon.MAC.macJointSequence_eq

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      {Ω : Type u_1} {α₁ : Type u_2} {α₂ : Type u_3} {β : Type u_4} (X1s : ℕ → Ω → α₁) (X2s : ℕ → Ω → α₂) (Ys : ℕ → Ω → β) :
      Used by
        theorem

        InformationTheory.Shannon.MAC.measurable_macJointSequence

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        {Ω : Type u_1} [MeasurableSpace Ω] {α₁ : Type u_2} {α₂ : Type u_3} {β : Type u_4} [MeasurableSpace α₁] [MeasurableSpace α₂] [MeasurableSpace β] (X1s : ℕ → Ω → α₁) (X2s : ℕ → Ω → α₂) (Ys : ℕ → Ω → β) (hX1s : ∀ (i : ℕ), Measurable (X1s i)) (hX2s : ∀ (i : ℕ), Measurable (X2s i)) (hYs : ∀ (i : ℕ), Measurable (Ys i)) (i : ℕ) :
        Used by
          noncomputable def

          InformationTheory.Shannon.MAC.macJointlyTypicalSet

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          {Ω : Type u_1} [MeasurableSpace Ω] {α₁ : Type u_2} {α₂ : Type u_3} {β : Type u_4} [Fintype α₁] [MeasurableSpace α₁] [Fintype α₂] [MeasurableSpace α₂] [Fintype β] [MeasurableSpace β] (μ : MeasureTheory.Measure Ω) (X1s : ℕ → Ω → α₁) (X2s : ℕ → Ω → α₂) (Ys : ℕ → Ω → β) (n : ℕ) (ε : ℝ) :
          Set ((Fin n → α₁) × (Fin n → α₂) × (Fin n → β))

          The three-way jointly typical set A_ε^n ⊆ (Fin n → α₁) × (Fin n → α₂) × (Fin n → β): triples (x₁, x₂, y) that are simultaneously typical along every single axis, every pair of axes, and the three-way joint axis. The seven conditions are exactly what the three achievability error events E1/E2/E3 require.

          @audit:ok

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          • One or more equations did not get rendered due to their size.
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              theorem

              InformationTheory.Shannon.MAC.mem_macJointlyTypicalSet_iff

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              {Ω : Type u_1} [MeasurableSpace Ω] {α₁ : Type u_2} {α₂ : Type u_3} {β : Type u_4} [Fintype α₁] [MeasurableSpace α₁] [Fintype α₂] [MeasurableSpace α₂] [Fintype β] [MeasurableSpace β] (μ : MeasureTheory.Measure Ω) (X1s : ℕ → Ω → α₁) (X2s : ℕ → Ω → α₂) (Ys : ℕ → Ω → β) (n : ℕ) (ε : ℝ) (x1 : Fin n → α₁) (x2 : Fin n → α₂) (y : Fin n → β) :
              (x1, x2, y) ∈ macJointlyTypicalSet μ X1s X2s Ys n ε ↔ x1 ∈ typicalSet μ X1s n ε ∧ x2 ∈ typicalSet μ X2s n ε ∧ y ∈ typicalSet μ Ys n ε ∧ (fun (i : Fin n) => (x1 i, x2 i)) ∈ typicalSet μ (ChannelCoding.jointSequence X1s X2s) n ε ∧ (fun (i : Fin n) => (x1 i, y i)) ∈ typicalSet μ (ChannelCoding.jointSequence X1s Ys) n ε ∧ (fun (i : Fin n) => (x2 i, y i)) ∈ typicalSet μ (ChannelCoding.jointSequence X2s Ys) n ε ∧ (fun (i : Fin n) => (x1 i, x2 i, y i)) ∈ typicalSet μ (macJointSequence X1s X2s Ys) n ε
              Used by
                theorem

                InformationTheory.Shannon.MAC.measurableSet_macJointlyTypicalSet

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                {Ω : Type u_1} [MeasurableSpace Ω] {α₁ : Type u_2} {α₂ : Type u_3} {β : Type u_4} [Fintype α₁] [MeasurableSpace α₁] [MeasurableSingletonClass α₁] [Fintype α₂] [MeasurableSpace α₂] [MeasurableSingletonClass α₂] [Fintype β] [MeasurableSpace β] [MeasurableSingletonClass β] (μ : MeasureTheory.Measure Ω) (X1s : ℕ → Ω → α₁) (X2s : ℕ → Ω → α₂) (Ys : ℕ → Ω → β) (n : ℕ) (ε : ℝ) :
                MeasurableSet (macJointlyTypicalSet μ X1s X2s Ys n ε)
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                  theorem

                  InformationTheory.Shannon.MAC.macJointlyTypicalSet_finite

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                  {Ω : Type u_1} [MeasurableSpace Ω] {α₁ : Type u_2} {α₂ : Type u_3} {β : Type u_4} [Fintype α₁] [MeasurableSpace α₁] [Fintype α₂] [MeasurableSpace α₂] [Fintype β] [MeasurableSpace β] (μ : MeasureTheory.Measure Ω) (X1s : ℕ → Ω → α₁) (X2s : ℕ → Ω → α₂) (Ys : ℕ → Ω → β) (n : ℕ) (ε : ℝ) :
                  (macJointlyTypicalSet μ X1s X2s Ys n ε).Finite
                  Used by
                    theorem

                    InformationTheory.Shannon.MAC.macJointlyTypicalSet_prob_tendsto_one

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                    {Ω : Type u_1} [MeasurableSpace Ω] {α₁ : Type u_2} {α₂ : Type u_3} {β : Type u_4} [Fintype α₁] [MeasurableSpace α₁] [MeasurableSingletonClass α₁] [Fintype α₂] [MeasurableSpace α₂] [MeasurableSingletonClass α₂] [Fintype β] [MeasurableSpace β] [MeasurableSingletonClass β] (μ : MeasureTheory.Measure Ω) [MeasureTheory.IsProbabilityMeasure μ] (X1s : ℕ → Ω → α₁) (X2s : ℕ → Ω → α₂) (Ys : ℕ → Ω → β) (hX1s : ∀ (i : ℕ), Measurable (X1s i)) (hX2s : ∀ (i : ℕ), Measurable (X2s i)) (hYs : ∀ (i : ℕ), Measurable (Ys i)) (hindep1 : Pairwise fun (i j : ℕ) => ProbabilityTheory.IndepFun (X1s i) (X1s j) μ) (hident1 : ∀ (i : ℕ), ProbabilityTheory.IdentDistrib (X1s i) (X1s 0) μ μ) (hindep2 : Pairwise fun (i j : ℕ) => ProbabilityTheory.IndepFun (X2s i) (X2s j) μ) (hident2 : ∀ (i : ℕ), ProbabilityTheory.IdentDistrib (X2s i) (X2s 0) μ μ) (hindep3 : Pairwise fun (i j : ℕ) => ProbabilityTheory.IndepFun (Ys i) (Ys j) μ) (hident3 : ∀ (i : ℕ), ProbabilityTheory.IdentDistrib (Ys i) (Ys 0) μ μ) (hindep4 : Pairwise fun (i j : ℕ) => ProbabilityTheory.IndepFun (ChannelCoding.jointSequence X1s X2s i) (ChannelCoding.jointSequence X1s X2s j) μ) (hident4 : ∀ (i : ℕ), ProbabilityTheory.IdentDistrib (ChannelCoding.jointSequence X1s X2s i) (ChannelCoding.jointSequence X1s X2s 0) μ μ) (hindep5 : Pairwise fun (i j : ℕ) => ProbabilityTheory.IndepFun (ChannelCoding.jointSequence X1s Ys i) (ChannelCoding.jointSequence X1s Ys j) μ) (hident5 : ∀ (i : ℕ), ProbabilityTheory.IdentDistrib (ChannelCoding.jointSequence X1s Ys i) (ChannelCoding.jointSequence X1s Ys 0) μ μ) (hindep6 : Pairwise fun (i j : ℕ) => ProbabilityTheory.IndepFun (ChannelCoding.jointSequence X2s Ys i) (ChannelCoding.jointSequence X2s Ys j) μ) (hident6 : ∀ (i : ℕ), ProbabilityTheory.IdentDistrib (ChannelCoding.jointSequence X2s Ys i) (ChannelCoding.jointSequence X2s Ys 0) μ μ) (hindep7 : Pairwise fun (i j : ℕ) => ProbabilityTheory.IndepFun (macJointSequence X1s X2s Ys i) (macJointSequence X1s X2s Ys j) μ) (hident7 : ∀ (i : ℕ), ProbabilityTheory.IdentDistrib (macJointSequence X1s X2s Ys i) (macJointSequence X1s X2s Ys 0) μ μ) {ε : ℝ} (hε : 0 < ε) :
                    Filter.Tendsto (fun (n : ℕ) => μ {ω : Ω | (jointRV X1s n ω, jointRV X2s n ω, jointRV Ys n ω) ∈ macJointlyTypicalSet μ X1s X2s Ys n ε}) Filter.atTop (nhds 1)

                    Bound (a): three-way joint AEP probability. The probability that the correct codeword triple (X₁ⁿ, X₂ⁿ, Yⁿ) lies in the three-way jointly typical set tends to 1.

                    The seven typicality conditions (three single-axis, three pairwise, one three-way) each hold with probability tending to 1 by the single-sequence AEP (InformationTheory.Shannon.typicalSet_prob_tendsto_one); their intersection then tends to 1 by the complement-union bound. The independence / identical-distribution hypotheses are stated separately for each of the seven sub-sequences, matching the single-user jointlyTypicalSet_prob_tendsto_one template.

                    Used by