Ultra-Reliable and Low Latency Communication in mmWave-Enabled Massive MIMO Networks

Vu, Trung Kien; Liu, Chen-Feng; Bennis, Mehdi; Debbah, Mérouane; Latva-aho, Matti; Hong, Choong Seon

doi:10.1109/lcomm.2017.2705148

Cited by 111 publications

(74 citation statements)

References 13 publications

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“…The tightened bound is almost identical to the looser bound in (23), up to a shrinking scale factor in the expression (27). Note that the value of J can be obtained either by solving for a zero derivative of function on the right hand side of (28), or by using a simple gradient ascent method.…”

Section: B Time Overflowmentioning

confidence: 80%

Outage of Periodic Downlink Wireless Networks With Hard Deadlines

Jurdi

Khosravirad

Viswanathan

et al. 2019

IEEE Trans. Commun.

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We consider a downlink periodic wireless communications system where multiple access points (APs) cooperatively transmit packets to a number of devices, e.g. actuators in an industrial control system. Each period consists of two phases: an uplink training phase and a downlink data transmission phase. Each actuator must successfully receive its unique packet within a single transmission phase, else an outage is declared. Such an outage can be caused by two events: a transmission error due to transmission at a rate that the channel cannot actually support or time overflow, where the downlink data phase is too short given the channel conditions to successfully communicate all the packets. We determine closed-form expressions for the probability of time overflow when there are just two field devices, as well as the probability of transmission error for an arbitrary number of devices. Also, we provide upper and lower bounds on the time overflow probability for an arbitrary number of devices. We propose a novel variable-rate transmission method that eliminates time overflow. Detailed system-level simulations are used to identify system design guidelines, such as the optimal amount of uplink training time, as well as for benchmarking the proposed system design versus non-cooperative cellular, cooperative fixed-rate, and cooperative relaying.

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Section: B Time Overflowmentioning

confidence: 80%

Outage of Periodic Downlink Wireless Networks With Hard Deadlines

Jurdi

Khosravirad

Viswanathan

et al. 2019

IEEE Trans. Commun.

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show abstract

“…However, they are also fundamental tools in building the two other 5G services, i.e. massive machine type communications [36] and URLLC [37], [38].…”

Section: A the Benefits Of Massive Multi-antenna Systems For Urllcmentioning

confidence: 99%

Wireless Access in Ultra-Reliable Low-Latency Communication (URLLC)

Popovski

Stefanović

Nielsen

et al. 2019

IEEE Trans. Commun.

391

216

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The future connectivity landscape and, notably, the 5G wireless systems will feature Ultra-Reliable Low Latency Communication (URLLC). The coupling of high reliability and low latency requirements in URLLC use cases makes the wireless access design very challenging, in terms of both the protocol design and of the associated transmission techniques. This paper aims to provide a broad perspective on the fundamental tradeoffs in URLLC as well as the principles used in building access protocols. Two specific technologies are considered in the context of URLLC: massive MIMO and multi-connectivity, also termed interface diversity. The paper also touches upon the important question of the proper statistical methodology for designing and assessing extremely high reliability levels.

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“…Depending on the specific form of the utility function f (·), closed-form solutions to (12) might not be available, but standard convex solvers can be used to find the optimal solutions.…”

Section: B Second Subproblem: Auxiliary Variablesmentioning

confidence: 99%

Dynamic Scheduling and Power Control in Uplink Massive MIMO with Random Data Arrivals

Chen

Björnson

Larsson

2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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In this paper, we study the joint power control and scheduling in uplink massive multiple-input multiple-output (MIMO) systems with random data arrivals. The data is generated at each user according to an individual stochastic process. Using Lyapunov optimization techniques, we develop a dynamic scheduling algorithm (DSA), which decides at each time slot the amount of data to admit to the transmission queues and the transmission rates over the wireless channel. The proposed algorithm achieves nearly optimal performance on the longterm user throughput under various fairness policies. Simulation results show that the DSA can improve the time-average delay performance compared to the state-of-the-art power control schemes developed for Massive MIMO with infinite backlogs.

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Ultra-Reliable and Low Latency Communication in mmWave-Enabled Massive MIMO Networks

Cited by 111 publications

References 13 publications

Outage of Periodic Downlink Wireless Networks With Hard Deadlines

Outage of Periodic Downlink Wireless Networks With Hard Deadlines

Wireless Access in Ultra-Reliable Low-Latency Communication (URLLC)

Dynamic Scheduling and Power Control in Uplink Massive MIMO with Random Data Arrivals

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