Pith Number

pith:E7ZPRYRH

pith:2026:E7ZPRYRHQYYYEKZUPJFD53JUQ3

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Sub-Band Full Duplex Resource Allocation: A Predictive Deep Reinforcement Learning Approach

Abdulla P, Abhiram D, Aiswarya Rajan, Arin Shemeem, Vipindev Adat Vasudevan

A hybrid Bi-LSTM and DDQN framework enables proactive sub-band allocation in SBFD systems by using traffic forecasts to guide real-time decisions.

arxiv:2605.14339 v1 · 2026-05-14 · cs.NI

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

The proposed predictive deep reinforcement learning framework significantly enhances the efficiency and adaptability of SBFD systems, making it a strong candidate for autonomous resource management in future 6G networks.

C2weakest assumption

The Bi-LSTM predictions remain accurate on unseen real-world traffic patterns and the DDQN agent converges to stable policies without excessive overhead or instability in live deployments.

C3one line summary

Hybrid Bi-LSTM and DDQN framework predicts traffic and allocates resources to improve spectrum utilization and reduce queues in sub-band full duplex networks.

References

15 extracted · 15 resolved · 0 Pith anchors

[1] Augmented reality with mobility awareness in mobile edge computing over 6g network: A survey, 2023

[2] Augmented and virtual reality services supported by 6g for improving smart cities, 2024

[3] The road towards 6g: A comprehensive survey, 2021

[4] Performance analysis of subband full duplex for 5g-advanced and 6g networks through simulations and field tests, 2023

[5] Subband full-duplex large-scale deployed network designs and tradeoffs, 2024

Receipt and verification

First computed	2026-05-17T23:39:08.206677Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

27f2f8e2278631822b347a4a3eed3486f2709bb543ad8a3067e5cb3a1cc9c828

Aliases

arxiv: 2605.14339 · arxiv_version: 2605.14339v1 · doi: 10.48550/arxiv.2605.14339 · pith_short_12: E7ZPRYRHQYYY · pith_short_16: E7ZPRYRHQYYYEKZU · pith_short_8: E7ZPRYRH

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/E7ZPRYRHQYYYEKZUPJFD53JUQ3 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 27f2f8e2278631822b347a4a3eed3486f2709bb543ad8a3067e5cb3a1cc9c828

Canonical record JSON

{
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    "abstract_canon_sha256": "d408ec3e7420d5bd3013d3373cae874061e040abdd8faf220faa9002938c4afb",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.NI",
    "submitted_at": "2026-05-14T04:03:16Z",
    "title_canon_sha256": "95ca196e5d0a0ca067d3692a7127ce3bf4c13c7f42d31e06d4e1797fc90e9380"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14339",
    "kind": "arxiv",
    "version": 1
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}