A 5G New Radio-Based Terrestrial Broadcast Mode: System Design and Field Trial

Richter, Lucca; Reimers, Ulrich

doi:10.1109/tbc.2022.3154601

Cited by 11 publications

(3 citation statements)

References 16 publications

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“…In the newly added protocol layer, Service Data Adaptation Protocol (SDAP), the traffic data for different MBS services would be mapped to different MBS bearers so that the lower layer protocols could handle the priority better. Several topics, including more flexible network structure, deployment, resource usage, and field trial, are further studied to meet the requirements for multicast and broadcast applications in the future [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Priority-Aware Resource Allocation for 5G mmWave Multicast Broadcast Services

Lin

et al. 2023

IEEE Trans. on Broadcast.

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5G Multicast Broadcast Services (MBS) are viewed as a promising 5G New Radio (NR) application, as standardization begins in 3GPP Release 17. With MBS, one next generation Node B (gNB) delivers data to multiple user equipments (UE) simultaneously, thus improving spectrum efficiency. Millimeter wave (mmWave) beamforming further enhances system performance by focusing signals in a dedicated direction. However, despite the advantages, we identify three issues of multicast with beamforming techniques. First, link directionality causes the gNB to transmit data over the beams sequentially, resulting in a combinatorial resource allocation problem. Confronting this beam scheduling issue, we develop an optimization algorithm that obtains an optimal solution in polynomial time. Second, UEs may falsely report their valuations over beam resources to gain more utility. Under this scenario, the gNB cannot allocate the resources to those in need due to the lack of accurate UE information. Therefore, we propose a Vickrey-Clarke-Groves (VCG) auction-based mechanism to incentivize the UEs to reveal their valuations over resources truthfully. This mechanism guarantees solution efficiency and maximizes social welfare. Third, as 3GPP standards allow for different priorities for different multicast flows, and video content providers distinguish between ordinary and premium UEs, we take UE priority into account. In this regard, we extend the valuation-based mechanism to a multipriority one. Finally, the mathematical analysis validates some desirable properties of the proposed scheme, such as incentivecompatibility. Simulation results also justify our superior performance in the 5G MBS system compared with other resource allocation schemes.

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Section: Introductionmentioning

confidence: 99%

Priority-Aware Resource Allocation for 5G mmWave Multicast Broadcast Services

Lin

et al. 2023

IEEE Trans. on Broadcast.

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“…Smart cities are nowadays enjoying a wide range of brand new telecommunication services enabled by last generation 5G networks [10], [33], [35], [37], [39], [40]. However, within this ultramodern context, older and more traditional broadcasting services like television and radio are still considered critical by many governments, since they support a cheap, easy and democratic access to information to all the population.…”

Section: Introductionmentioning

confidence: 99%

Green and robust optimal design of Single Frequency Networks by min-max regret and ACO-based learning

D’Andreagiovanni

Lakhlef

Nardin

2022

2022 IEEE International Smart Cities Conference (ISC2)

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Notwithstanding the introduction of brand new 5Gbased wireless services, single frequency networks supporting digital television and radio broadcasting still represent a major source of telecommunications services in modern smart cities. In this work, we propose a robust optimization model for the green design of second generation single frequency networks based on the digital television DVB-T standard, whose ongoing adoption requires to reconfigure and redesign existing networks. Our robust model aims at protecting design solutions against the data uncertainty that naturally affect propagation of signals in a real environment. For reducing conservatism of solutions, we refer to a heuristic min-max regret paradigm and to solve the resulting problem we propose to adopt a hybrid exact-heuristic algorithm based on the combination of an Ant Colony Optimizationlike learning procedure, exploiting tight formulations of the optimization model, with an exact large neighborhood search. Results of computational tests considering realistic instances show that the heuristic min-max regret approach can produce solutions characterized by a substantially lower price of robustness without sacrificing protection against data uncertainty.

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“…Based on specialized hardware platforms such as ASIC and FPGA, the decoding throughput performance of LDPC decoders can be extremely high [10][11][12][13] but also bring a high development cost. Different from traditional development methods, soft-defined radio (SDR) technology offers a software-based solution for many hardware devices in communication systems [14,15]. This software solution considerably reduces the hardware resources and development time necessary for the deployment of radio-based communications systems, and it can be very useful when testing protocols, prototypes, and applications in a simple and economical way.…”

Section: Introductionmentioning

confidence: 99%

Multi-Gbps LDPC Decoder on GPU Devices

Dai

Yin

et al. 2022

Electronics

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To meet the high throughput requirement of communication systems, the design of high-throughput low-density parity-check (LDPC) decoders has attracted significant attention. This paper proposes a high-throughput GPU-based LDPC decoder, aiming at the large-scale data process scenario, which optimizes the decoder from the perspectives of the decoding parallelism and data scheduling strategy, respectively. For decoding parallelism, the intra-codeword parallelism is fully exploited by combining the characteristics of the flooding-based decoding algorithm and GPU programming model, and the inter-codeword parallelism is improved using the single-instruction multiple-data (SIMD) instructions. For the data scheduling strategy, the utilization of off-chip memory is optimized to satisfy the demands of large-scale data processing. The experimental results demonstrate that the decoder achieves 10 Gbps throughput by incorporating the early termination mechanism on general-purpose GPU (GPGPU) devices and can also achieve a high-throughput and high-power-efficiency performance on low-power embedded GPU (EGPU) devices. Compared with the state-of-the-art work, the proposed decoder had a × 1.787 normalized throughput speedup at the same error correcting performance.

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A 5G New Radio-Based Terrestrial Broadcast Mode: System Design and Field Trial

Cited by 11 publications

References 16 publications

Priority-Aware Resource Allocation for 5G mmWave Multicast Broadcast Services

Priority-Aware Resource Allocation for 5G mmWave Multicast Broadcast Services

Green and robust optimal design of Single Frequency Networks by min-max regret and ACO-based learning

Multi-Gbps LDPC Decoder on GPU Devices

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