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1. Low-Overhead Distributed MAC for Serving Dynamic Users over Multiple Channels

   https://doi.org/10.23919/WiOpt52861.2021.9589394  

   Zhou, Xujin; Koprulu, Irem; Eryilmaz, Atilla; Neely, Michael J. (October 2021, Proc. 19th internatinoal symposium on modeling and optimization in mobile, ad hoc, and wireless networks (WiOpt))

   With the adoption of 5G wireless technology and the Internet-of-Things (IoT) networking, there is a growing interest in serving a dense population of low-complexity devices over shared wireless uplink channels. Different from the traditional scenario of persistent users, in these new networks each user is expected to generate only small bundles of information intermittently. The highly dynamic nature of such demand and the typically low-complexity nature of the user devices calls for a new MAC paradigm that is geared for low-overhead and distributed operation of dynamic users.In this work, we address this need by developing a generic MAC mechanism for estimating the number and coordinating the activation of dynamic users for efficient utilization of the time-frequency resources with minimal public feedback from the common receiver. We fully characterize the throughput and delay performance of our design under a basic threshold-based multi-channel capacity condition, which allows for the use of different channel utilization schemes. Moreover, we consider the Successive-Interference-Cancellation (SIC) Multi-Channel MAC scheme as a specific choice in order to demonstrate the performance of our design for a spectrally-efficient (albeit idealized) scheme. Under the SIC encoding/decoding scheme, we prove that our low-overhead distributed MAC can support maximum throughput, which establishes the efficiency of our design. Under SIC, we also demonstrate how the basic threshold-based success model can be relaxed to be adapted to the performance of a non-ideal success model. 

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2. An Exploration of the Heterogeneous Unsourced MAC

   https://doi.org/10.1109/IEEECONF53345.2021.9723339  

   Rini, S; Amalladinne, V K; Chamberland, J-F (October 2021, IEEE)

   The unsourced multiple access channel (MAC) model was originally introduced to study the communication scenario in which a number of devices with low-complexity and low-energy wish to upload their respective messages to a base station. In the original problem formulation, all devices communicate using the same information rate: this may be very inefficient in certain wireless situations with varied channel conditions, power budgets, and payload requirements at the devices. This paper extends the original problem setting to allow for heterogeneous transmissions. More specifically, we consider the scenario in which devices are clustered into two classes with different signal-to-noise ratio (SNR) levels and payload requirements. In the cluster with higher power, devices transmit using a two-layer superposition modulation. In the cluster with lower energy, users transmit with the same base constellation as in the high power cluster. Within each layer, devices employ the same codebook. At the receiver, signal groupings are recovered using Coded Compressed Sensing (CCS) decoder. An outer code is further employed to stitch fragments together across times and layers, as needed. This pragmatic approach to heterogeneous CCS is validated numerically and design guidelines are identified. 

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3. Analysis of Joint Scheduling and Power Control for Predictable URLLC in Industrial Wireless Networks

   Wang, Ling; Zhang, Hongwei (January 2019, IEEE International Conference on Industrial Internet (ICII))

   Wireless networks are being applied in various industrial sectors, and they are posed to support mission-critical industrial IoT applications which require ultra-reliable, low-latency communications (URLLC). Ensuring predictable per-packet communication reliability is a basis of predictable URLLC, and scheduling and power control are two basic enablers. Scheduling and power control, however, are subject to challenges such as harsh environments, dynamic channels, and distributed network settings in industrial IoT. Existing solutions are mostly based on heuristic algorithms or asymptotic analysis of network performance, and there lack field-deployable algorithms for ensuring predictable per-packet reliability. Towards addressing the gap, we examine the cross-layer design of joint scheduling and power control and analyze the associated challenges. We introduce the Perron–Frobenius theorem to demonstrate that scheduling is a must for ensuring predictable communication reliability, and by investigating characteristics of interference matrices, we show that scheduling with close-by links silent effectively constructs a set of links whose required reliability is feasible with proper transmission power control. Given that scheduling alone is unable to ensure predictable communication reliability while ensuring high throughput and addressing fast-varying channel dynamics, we demonstrate how power control can help improve both the reliability at each time instant and throughput in the long-term. Based on the analysis, we propose a candidate framework of joint scheduling and power control, and we demonstrate how this framework behaves in guaranteeing per-packet communication reliability in the presence of wireless channel dynamics of different time scales. Collectively, these findings provide insight into the cross-layer design of joint scheduling and power control for ensuring predictable per-packet reliability in the presence of wireless network dynamics and uncertainties. 

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4. OFDM Pilot-Based Radar for Joint Vehicular Communication and Radar Systems

   https://doi.org/10.1109/VNC.2018.8628347  

   Ozkaptan, Ceyhun D.; Ekici, Eylem; Altintas, Onur; Wang, Chang-Heng (December 2018, 2018 IEEE Vehicular Networking Conference (VNC))

   With the large-scale deployment of connected and autonomous vehicles, the demand on wireless communication spectrum increases rapidly in vehicular networks. Due to increased demand, the allocated spectrum at the 5.9 GHz band for vehicular communication cannot be used efficiently for larger payloads to improve cooperative sensing, safety, and mobility. To achieve higher data rates, the millimeter-wave (mmWave) automotive radar spectrum at 76-81 GHz band can be exploited for communication. However, instead of employing spectral isolation or interference mitigation schemes between communication and radar, we design a joint system for vehicles to perform both functions using the same waveform. In this paper, we propose radar processing methods that use pilots in the orthogonal frequency-division multiplexing (OFDM) waveform. While the radar receiver exploits pilots for sensing, the communication receiver can leverage pilots to estimate the time-varying channel. The simulation results show that proposed radar processing can be efficiently implemented and meet the automotive radar requirements. We also present joint system design problems to find optimal resource allocation between data and pilot subcarriers based on radar estimation accuracy and effective channel capacity. 

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5. Time-Shift Coding for Uncoordinated MACs

   https://doi.org/10.1109/LATINCOM59467.2023.10361874  

   Yuan, Peihong; Duffy, Ken R; Médard, Muriel (November 2023, IEEE LatinAmerican Conference on Communications)

   In this work, we discuss time-shift coding and GRAND ZigZag decoding for uncoordinated multiple access channels (MACs). Time-shift coding relies on the delay difference of the received packets to prevent fully overlapped collisions. Users transmit with different time-shifts in designated time slots until the receiver successfully decodes all messages. At the receiver side, ZigZag decoding is employed to separate packets with linear complexity in noiseless scenarios. For cases with noise, a guessing random additive noise decoding (GRAND)-based algorithm is utilized to identify the most probable noise vector in conjunction with ZigZag decoding. Simulation results demonstrate that time-shift coding significantly reduces collision probabilities, thereby enhancing system throughput in noiseless scenarios. In the context of Gaussian MAC, the GRAND ZigZag decoding method outperforms successive interference cancellation (SIC)-based schemes in high signal-to-noise ratio (SNR) regimes. 

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