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1. Low-Latency Preamble-Free Transmission of Short Messages via Quickest Change Detection

   Bischoff, G; Wang, C-C (June 2025, IEEE)

   The latency and control overhead of sending the preamble in synchronous communications can be excessive when transmitting short sensing/control messages. To reduce these overheads, this work proposes a preamble-free solution based on the framework of quickest change detection. Specific contributions include a joint decoding/demodulation scheme that is provably asymptotically optimal, and a more practical CuSum-like implementation. Numerical results show that the proposed scheme reduces the latency by 47%–79% when compared to the preamble-based solutions. The scheme is also inherently robust and automatically adapts to any unknown underlying SNRs. 

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2. Full-Duplex Store-Carry-Forward scheme for Intermittently Connected Vehicular Networks

   https://doi.org/10.1109/VTC2020-Spring48590.2020.9129598  

   Siddig, Ali A.; Ibrahim, Ahmed S.; Ismail, Mahmoud H. (May 2020, 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring))

   We consider intermittently connected vehicular networks (ICVNs) in which base stations (BSs) are installed along the highway to connect moving vehicles with internet. Due to the deployment cost, it is hard to cover the entire highway with BSs. To minimize the outage time in the uncovered area (UA), several cooperative store-carry-forward (CSCF) schemes have been proposed in which a vehicle is selected to act as a relay by buffering data to be relayed to a target vehicle in the UA. In this paper, we propose an energy-efficient full-duplex (FD) CSCF scheme that exploits the relay ability to receive and transmit simultaneously to improve the effective communication time, Te, between the relay and the target vehicle. Accordingly, it can minimize the outage time and deliver more data to the the target vehicle. In addition, the power allocation that minimizes the transmission cost (TC) under the required rates constraints is found. The problem is formulated as a geometric program (GP) and globally solved using the interior-point method. As compared to the half-duplex CSCF scheme, simulation results show that the proposed FD scheme offers more effective time, more successfully delivered data in the UA and lower TC. 

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3. Distributed Power Allocation for 6-GHz Unlicensed Spectrum Sharing via Multi-agent Deep Reinforcement Learning

   https://doi.org/10.1109/ICIT58465.2023.10143125  

   Zhang, Xiang; Bhuyan, Arupjyoti; Kasera, Sneha Kumar; Ji, Mingyue (April 2023, 2023 IEEE International Conference on Industrial Technology (ICIT))

   We consider the problem of spectrum sharing by multiple cellular operators. We propose a novel deep Reinforcement Learning (DRL)-based distributed power allocation scheme which utilizes the multi-agent Deep Deterministic Policy Gradient (MA-DDPG) algorithm. In particular, we model the base stations (BSs) that belong to the multiple operators sharing the same band, as DRL agents that simultaneously determine the transmit powers to their scheduled user equipment (UE) in a synchronized manner. The power decision of each BS is based on its own observation of the radio environment (RF) environment, which consists of interference measurements reported from the UEs it serves, and a limited amount of information obtained from other BSs. One advantage of the proposed scheme is that it addresses the single-agent non-stationarity problem of RL in the multi-agent scenario by incorporating the actions and observations of other BSs into each BS's own critic which helps it to gain a more accurate perception of the overall RF environment. A centralized-training-distributed-execution framework is used to train the policies where the critics are trained over the joint actions and observations of all BSs while the actor of each BS only takes the local observation as input in order to produce the transmit power. Simulation with the 6 GHz Unlicensed National Information Infrastructure (U-NII)-5 band shows that the proposed power allocation scheme can achieve better throughput performance than several state-of-the-art approaches. 

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4. Improved Abstraction for Clear Channel Assessment in ns-3 802.11 WLAN Model

   https://doi.org/10.1145/3321349.3321353  

   Lanante, Leonardo; Roy, Sumit; Carpenter, Scott E.; Deronne, Sébastien (January 2019, Proc. 2019 Workshop on ns-3)

   An important challenge for ns-3 is to enable efficient performance evaluation of increasingly dense and heterogeneous networks,cognizant of cross-layer (specifically, Layers 1 & 2) interactions. In this work(a continuation of U.Washington efforts),we present improved physical layer abstractions for a key component underlying all 802.11 WLAN MAC performance evaluation-the Clear Channel Assessment(CCA) procedure central to CSMA/CA-for implementation in the ns-3 simulator. We model the preamble correlation process as typically implemented in 802.11 radio and represent the resulting probability of detection as a look-up table with a parameterized correlation threshold for different receive sensitivity strategies. Further, we also added a new carrier sense threshold adjustment mechanism to allow nodes to enable bypassing the default(and to date,fixed) -82dBm threshold. Such a capability aligns ns-3 for performance evaluation of dense networks equipped with new spatial reuse mechanisms. We demonstrate this via simulation of spatial reuse gains from dynamic sensitivity control(DSC) that are verified against IEEE 802.11ax standards group contributions. Using simulation results from a fixed rate multi-BSS network,we then identify valuable design guidelines to maximize the aggregate throughput with DSC. 

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5. Forward-Private Dynamic Searchable Symmetric Encryption with Efficient Search

   https://doi.org/10.1109/ICC.2018.8422480  

   Ozmen, Muslum Ozgur; Hoang, Thang; Yavuz, Attila A. (May 2018, 2018 IEEE International Conference on Communications (ICC))

   Dynamic Searchable Symmetric Encryption (DSSE) allows to delegate keyword search and file update over an encrypted database via encrypted indexes, and therefore provides opportunities to mitigate the data privacy and utilization dilemma in cloud storage platforms. Despite its merits, recent works have shown that efficient DSSE schemes are vulnerable to statistical attacks due to the lack of forward-privacy, whereas forward-private DSSE schemes suffers from practicality concerns as a result of their extreme computation overhead. Due to significant practical impacts of statistical attacks, there is a critical need for new DSSE schemes that can achieve the forward-privacy in a more practical and efficient manner. We propose a new DSSE scheme that we refer to as Forward-private Sublinear DSSE (FS-DSSE). FS-DSSE harnesses special secure update strategies and a novel caching strategy to reduce the computation cost of repeated queries. Therefore, it achieves forward-privacy, sublinear search complexity, low end-to-end delay, and parallelization capability simultaneously. We fully implemented our proposed method and evaluated its performance on a real cloud platform. Our experimental evaluation results showed that the proposed scheme is highly secure and highly efficient compared with state-of-the-art DSSE techniques. Specifically, FS-DSSE is up to three magnitude of times faster than forward-secure DSSE counterparts, depending on the frequency of the searched keyword in the database. 

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