Channel and question
- Input
- Independent inputs \(X_1,X_2\) with powers \(P_1,P_2\).
- Output
- \(Y=X_1+X_2+Z\)
- Law
- \(Z\sim\mathcal N(0,N)\) iid.
- Quantity
- Capacity region \(\mathcal C_{\mathrm{GMAC}}\), measured in rate pairs in bits per channel use.
Criterion. Vanishing average joint decoding error. Resource averaging is fixed by the explicit model assumption below.
- Messages are independent.
- There is no feedback.
- For user j and every local message m_j, sum_t x_{j,t}(m_j)^2 <= n P_j. There is no averaging over messages and no feedback.
Parameters
- \(P_1,P_2\)
- User power constraints. Range: \(P_1,P_2\ge0\).
- \(N\)
- Noise variance. Range: \(N>0\).
Current status
| Result | Relation | Method | Year |
|---|---|---|---|
| Inner Region | \(R_i\le\frac12\log_2(1+P_i/N),\ R_1+R_2\le\frac12\log_2(1+(P_1+P_2)/N)\) | Independent Gaussian codebooks and joint decoding. | 1971 |
| Outer Region | \(R_i\le\frac12\log_2(1+P_i/N),\ R_1+R_2\le\frac12\log_2(1+(P_1+P_2)/N)\) | Gaussian entropy maximization in the MAC converse. | 1972 |
Formal verification
Concrete operational definitions and admitted research statements are present. Existing proofs are preserved. New statements require mathematical review and proof completion. Power convention: SeparateCodewordPowerAdmissible. No equivalence to another power convention is assumed.
Claims
- The Gaussian MAC capacity region under separate maximum-codeword power constraints.
operational-capacity· exact capacity · solved · Formally stated · v1
Lean declarations (1)
CapacityAtlas.Claims.gaussianMACclaim · operational-capacity
lean/CapacityAtlas/Claims/GaussianMAC.lean — The Gaussian MAC capacity region under separate maximum-codeword power constraints.
References
- Rudolf Ahlswede (1973). Multi-way communication channels. Proceedings of the Second International Symposium on Information Theory (September 1971), Akadémiai Kiadó, pp. 23–52.
- Henry Herng-Jiunn Liao (1972). Multiple Access Channels. PhD thesis, University of Hawaii.
- Abbas El Gamal and Young-Han Kim (2011). Network Information Theory. Cambridge University Press. DOI 10.1017/CBO9781139030687.