A Broadcast Approach Maha Zohdy, Ali Tajer, Shlomo Shamai RPI RPI - - PowerPoint PPT Presentation

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Jun 03, 2023 158 likes •365 views

Interference Management without CSIT: A Broadcast Approach Maha Zohdy, Ali Tajer, Shlomo Shamai RPI RPI Technion ISIT'20 1 6/7/2020 Interference Channel Interference Avoidance Interference management Interference Cancellation under

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Interference Management without CSIT: A Broadcast Approach

Maha Zohdy, Ali Tajer, Shlomo Shamai

RPI

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Technion RPI

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Interference Channel

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Interference Avoidance
Interference Cancellation
Interference Coordination

Interference management under lack of CSIT

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Related Literature

Full CSIT

Best inner bound on IC capacity with full CSIT (Han & Kobayashi’81)
HK scheme achieves capacity within 1-bit (Etkin, David, & Wang’08)

No CSIT in high SNR regime

Blind interference alignment (Jafar’ 12)
Impact of topology on blind IA (Naderializadeh & Avestimehr,’14)
Binary ergodic IC (Maddah-Ali, Avestimehr, & Zhu’17)

No CSIT in non-asymptotic regime

Erasure IC (Zhu & Shen’16)
Degraded IC (Raja, Prabhakaran, & Viswanath’09)
Approximate capacity for fast fading IC (Sebastian, Karakus, & Diggavi’18)

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CSIT Uncertainty

Slowly fading channels

Receiver can acquire perfect CSI
Dynamic CSIT modeling: fixed + variable
No delay constraint: ergodic approach
Stringent delay constraint:

Outage approach Broadcast approach

No CSI at Tx
Fixed rate
Failure when channel not strong enough
No CSI at Tx
Rate adapted to actual channel
Partial success even for weak channels

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Related Literature

Broadcast approach

Proposed for compound channels (Cover’72)
Proposed for single-user Gaussian channel (Shamai’97)
Used in successive refinement of source coding (Remoldy’09)
Generalized to multi-antenna systems (Shamai & Stiener’03)

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Broadcast Approach to SU Channel

unknown to Tx

Single-user channel with ℓ −states

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Broadcast Approach to SU Channel

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Single-user channel with ℓ −states Codebook assignment Successive decoding

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Channel Model

Two-user IC with no CSIT

Each receiver is affected by both transmissions
Each transmitter is affected by combined network state
No CSIT at Tx; adapt broadcast approach to combined network state

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Channel Model

Two-user IC with two-state channel Channel input-output relationship:

Unknown to Tx1 Unknown to Tx2 Known to Rx

2-channel states:

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Normalized Channel Model

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Normalized two-user IC with two-state channel Channel input-output relationship: 3-channel states:

Unknown to Tx1 Unknown to Tx2 Known to Rx

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Adapting to Multiuser Channel

No unique way to order channel states! Adapt to multi-user channel

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Codebook Assignment

3-channel states: Codebook assignment

Normalized two-user channel with no CSIT

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User 1 User 2

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Average Rate Region

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Asymmetric channel

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Average Rate Region

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Asymmetric channel

User 1 User 2

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Gap to Sum-rate Capacity

Symmetric channel:

Theorem 2. For large asymptote of 𝑄 and any fixed channel state, the average sum-rate achievable by the proposed scheme lies within a finite gap to the sum-rate capacity of symmetric IC with full CSIT. The gap is bounded as follows

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Use HK sum-rate under power allocation in (Etkin, Tse, & Wang’08) Sum-rate capacity is known

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Capacity Approximation

Theorem 2. For large asymptote of 𝑄 any fixed channel state, the average sum-rate achievable by the proposed scheme lies within a finite gap to the sum-rate capacity of symmetric IC with full CSIT. The gap is bounded as follows

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First-order capacity approximation
Limit of ratio of sum-capacity to logarithm of SNR
DoF not lost without CSIT (1 for two-user IC)

Degrees of freedom (DoF)

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Average Sum-rate Gap

Symmetric channel

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Normalized gap Bound on gap

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Main Observations

Broadcast approach to two-user IC with no CSIT

Proposed novel BC scheme adapted to combined network state.
Characterized the resulting average achievable rate region.
Characterized gap to sum-rate capacity in the asymptote of high SNR.

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Possible extensions

Adapt BC approach to IC with local CSIT.
Identify most valuable subset of local CSIT.

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Thank you!

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References

T. Han and K. Kobayashi, “A new achievable rate region for the interference channel,” IEEE Transactions on

Information Theory, vol. 27, no. 1, pp. 49–60, Jan. 1981.

R. H. Etkin, N. David, and H. Wang, “Gaussian interference channel capacity to within one bit,” IEEE Transactions on

Information Theory, vol. 54, no. 12, pp. 5534–5562, Nov. 2008.

V. R. Cadambe and S. A. Jafar, “Interference alignment and degrees of freedom of the K-user interference channel,”

IEEE Transactions on Information Theory, vol. 54, no. 8, pp. 3425 – 3441, Jul. 2008.

T. Cover, “Broadcast channels,” IEEE Transactions on Information Theory, vol. 18, no. 1, pp. 2–14, Jan. 1972.
S. Shamai (Shitz), “A broadcast strategy for the Gaussian slowly fading channel,” in Proc. IEEE International

Symposium Information Theory, Ulm, Germany, Jun. 1997, p. 150.

S. Shamai (Shitz) and A. Steiner, “A broadcast approach for a single user slowly fading MIMO channel,” IEEE

Transactions on Information Theory, vol. 49, no. 10, pp. 2617–2635, Oct. 2003.

S. Kazemi and A. Tajer, “Multiaccess communication via a broadcast approach adapted to the multiuser channel,” IEEE

Transactions on Communications, vol. 66, no. 8, pp. 3341–3353, Feb. 2018.

M. Zohdy, A. Tajer, and S. Shamai (Shitz), “Broadcast approach to multiple access with local CSIT,” IEEE Transactions
n Communications, vol. 67, no. 11, pp. 7483–7498, Aug. 2019.