2018
DOI: 10.1109/tit.2018.2839643
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State-Dependent Gaussian Multiple Access Channels: New Outer Bounds and Capacity Results

Abstract: This paper studies a two-user state-dependent Gaussian multiple-access channel (MAC) with state noncausally known at one encoder. Two scenarios are considered: i) each user wishes to communicate an independent message to the common receiver, and ii) the two encoders send a common message to the receiver and the non-cognitive encoder (i.e., the encoder that does not know the state) sends an independent individual message (this model is also known as the MAC with degraded message sets).For both scenarios, new ou… Show more

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Cited by 6 publications
(7 citation statements)
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“…where f (•) is defined in (16). Proof: The corner point (27) follows from (17) and (19) (with ρ = 0), and (28) follows from (13) by setting R 2 = C 2 , and by taking δ → 0.…”
Section: Corner Pointsmentioning
confidence: 99%
See 2 more Smart Citations
“…where f (•) is defined in (16). Proof: The corner point (27) follows from (17) and (19) (with ρ = 0), and (28) follows from (13) by setting R 2 = C 2 , and by taking δ → 0.…”
Section: Corner Pointsmentioning
confidence: 99%
“…Due to space constraints, we have omitted the proofs of most results. They can be found in [16]. Theorem 1: The capacity region C(P 1 , P 2 , Q) of the dirty MAC (1) is outer-bounded by the region with rate pairs…”
Section: A New Outer Boundsmentioning
confidence: 99%
See 1 more Smart Citation
“…The type of channels with mismatched property has been addressed in the past for various models, for example, in [21][22][23][24][25], the state-dependent multiple access channel (MAC) is studied with the state known at only one transmitter. The best outer bound for the Gaussian MAC setting was recently reported in [26]. The point-to-point helper channel studied in [27,28] can be considered as a special case of [25], where the cognitive transmitter does not send any message.…”
Section: P Smentioning
confidence: 99%
“…where in the last equality we used the definition of Σ X 0 S from (26). Consequently, we established an upper bound on I(S n ; Y n 1 |M 1 ):…”
Section: Appendix C Optimal Coefficients For the Mimo Gaussian With mentioning
confidence: 99%