Coordinated User Scheduling in 5G Dynamic TDD Systems with Beamforming

Lukowa, Anna; Venkatasubramanian, Venkatkumar

doi:10.1109/pimrc.2018.8580681

Cited by 4 publications

(5 citation statements)

References 2 publications

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“…CLI mitigation and coordination schemes have therefore been widely investigated over recent prior art. In [10][11][12], coordinated cross-cell beam-forming, UL power control and cell muting are proposed to limit the residual network CLI, especially towards the more CLI-sensitive cell-edge UEs. Joint UL transceiver design [13][14][15], based on inter-cell signaling of the UEs' spatial signatures, is also introduced in order to isolate the BS-BS CLI spatial subspace from that is of the desired UL transmission.…”

Section: A State Of the Art Dynamic Tdd Studiesmentioning

confidence: 99%

“…• Unlike the state-of-the-art relevant TDD solutions [7][8][9][10][11][12][13][14][15][16][17][18][19], the proposed solution considers the joint capacity and latency statistics to optimize the URLLC outage latency performance. It is fully compliant with the current 3GPP 5G-NR standard specifications for dynamic-TDD deployments.…”

Section: Paper Contributionmentioning

confidence: 99%

“…Herein, for the sake of cross-scheme fairness, we adopt the same buffered traffic criterion of Algorithm-1 as per eq. (12). The structure of the selected radio pattern, in terms of the placement of the DL and UL symbols, is presumed to be always evenly distributed, and with a symbol block size of This work is licensed under a Creative Commons Attribution 4.0 License.…”

Section: State-of-the-art Duplexing Schemesmentioning

confidence: 99%

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Online Radio Pattern Optimization Based on Dual Reinforcement-Learning Approach for 5G URLLC Networks

2020

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The fifth generation (5G) radio access technology is designed to support highly delaysensitive applications, i.e., ultra-reliable and low-latency communications (URLLC). For dynamic time division duplex (TDD) systems, the real-time optimization of the radio pattern selection becomes of a vital significance in achieving decent URLLC outage latency. In this study, a dual reinforcement machine learning (RML) approach is developed for online pattern optimization in 5G new radio TDD deployments. The proposed solution seeks to minimizing the maximum URLLC tail latency, i.e., min-max problem, by introducing nested RML instances. The directional and real-time traffic statistics are monitored and given to the primary RML layer to estimate the sufficient number of downlink (DL) and uplink (UL) symbols across the upcoming radio pattern. The secondary RML sub-networks determine the DL and UL symbol structure which best minimizes the URLLC outage latency. The proposed solution is evaluated by extensive and highly-detailed system level simulations, where our results demonstrate a considerable URLLC outage latency improvement with the proposed scheme, compared to the state-of-the-art dynamic-TDD proposals.

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Section: A State Of the Art Dynamic Tdd Studiesmentioning

confidence: 99%

Section: Paper Contributionmentioning

confidence: 99%

Section: State-of-the-art Duplexing Schemesmentioning

confidence: 99%

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Online Radio Pattern Optimization Based on Dual Reinforcement-Learning Approach for 5G URLLC Networks

2020

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“…Accordingly, optimal BS-BS CLI cancellation [6] is discussed within 3GPP, where inter-cell full-packet exchange is assumed. Moreover, coordinated dynamic scheduling and beam-forming [7,8] are proposed to counteract the CLI by globalizing the BS scheduling decisions. Furthermore, joint beam-forming schemes are suggested [9,10] in order to control the inflicted inter-cell CLI in the spatial domain.…”

Section: Introductionmentioning

confidence: 99%

Cross-Link Interference Suppression By Orthogonal Projector For 5G Dynamic TDD URLLC Systems

Esswie¹,

Pedersen²

2020

2020 IEEE Wireless Communications and Networking Conference (WCNC)

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Dynamic time division duplexing (TDD) is envisioned as a vital transmission technology of the 5G new radio, due to its reciprocal propagation characteristics. However, the potential cross-link interference (CLI) imposes a fundamental limitation against the feasibility of the ultra-reliable and low latency communications (URLLC) in dynamic-TDD systems. In this work, we propose a near-optimal and complexity-efficient CLI suppression scheme using orthogonal spatial projection, while the signaling overhead is limited to B-bit, over the back-haul links. Compared to the state-of-the-art dynamic-TDD studies, proposed solution offers a significant improvement of the URLLC outage latency, e.g., ∼ −199% reduction, while boosting the achievable capacity per the URLLC packet by ∼ +156%.

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“…In [13][14][15], coordinated DL beam-forming and receiver design are proposed in order to isolate the subspace of the BS-BS CLI in the spatial domain from the useful signal subspace. Moreover, smarter dynamic UE scheduling and optimized power control [16] are essential to control the network CLI. Those schemes typically require an inter-BS coordination signaling overhead, e.g., for exchanging the UE-specific allocation information.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Outage Latency and Throughput Performance in Industrial Factory 5G TDD Deployments

Esswie¹,

Pedersen²

2020

Preprint

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The fifth generation (5G) new radio supports a diversity of network deployments. The industrial factory (InF) wireless automation use cases are emerging and drawing an increasing attention of the 5G new radio standardization groups. Therefore, in this paper, we propose a service-aware time division duplexing (TDD) frame selection framework for multitraffic deployments. We evaluate the performance of the InF network deployments with the state-of-the-art 3GPP modeling assumptions. In particular, we consider the dynamic TDD mode along with optimized uplink power control settings. Multi-traffic coexistence scenarios are also incorporated such that quality of service (QoS) aware dynamic user scheduling and TDD link selection are introduced. Extensive system level simulations are performed in order to evaluate the performance of the proposed solutions, where the proposed QoS-aware scheme shows 68% URLLC outage latency reduction compared to the QoS-unaware solutions. Finally, the paper offers insightful conclusions and design recommendations on the TDD radio frame selection, uplink power control settings and the best QoS-coexistence practices, in order to achieve a decent URLLC outage latency performance in the state-of-the-art InF deployments.

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Coordinated User Scheduling in 5G Dynamic TDD Systems with Beamforming

Cited by 4 publications

References 2 publications

Online Radio Pattern Optimization Based on Dual Reinforcement-Learning Approach for 5G URLLC Networks

Online Radio Pattern Optimization Based on Dual Reinforcement-Learning Approach for 5G URLLC Networks

Cross-Link Interference Suppression By Orthogonal Projector For 5G Dynamic TDD URLLC Systems

Analysis of Outage Latency and Throughput Performance in Industrial Factory 5G TDD Deployments

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