On the Analysis of Scheduling in Dynamic Duplex Multihop mmWave Cellular Systems

García-Rois, Juan; Gómez-Cuba, Felipe; Akdeniz, Mustafa Riza; González-Castaño, Francisco J.; Burguillo, Juan C.; Rangan, Sundeep; Lorenzo, Beatriz

doi:10.1109/twc.2015.2446983

Cited by 55 publications

(69 citation statements)

References 35 publications

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“…A possible solution is to deploy a dynamic duplex scheme to allow maximum resource allocated for users, as in contrast of static duplexing schemes (i.e. TDD and FDD) in current 4G network [82]. However, more solutions are still needed as well as field measurements validations.…”

Section: Open Problemsmentioning

confidence: 99%

5G roadmap: 10 key enabling technologies

et al. 2016

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Section: Open Problemsmentioning

confidence: 99%

5G roadmap: 10 key enabling technologies

et al. 2016

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“…In order to apply the existing NUM know-how to cellular systems the above results need revision. In [10] NUM for mmWave multi-hop heterogeneous cellular networks is considered without MU-MIMO, leaving out one key technology in cellular modern physical layers. Nevertheless, [10] produced two analyses with and without interference in the mmWave multi-hop picocellular system, showing that the effect of interference was negligible.…”

Section: A Related Workmentioning

confidence: 99%

“…As an evolution of current cellular systems, mmWave picocellular systems with large antenna arrays are a prime candidate to exploit MU-MIMO at the physical layer, while IAB RNs are required due to the limited ranges. Therefore, a complete scheduling model for future mmWave picocellular systems with IAB RNs should feature both multi-hop and MU-MIMO, and optimize the entire system treated as a mesh multi-hop network comprising wired-backhaul BSs, IAB RNs, and User Equipment (UE) [9], [10], and where simultaneous transmissions and receptions are possible. Unfortunately, most models in the literature considered either single-hop MU-MIMO [6]- [8], [11] or multi-hop omnidirectional singleantenna systems [12]- [16].…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we propose and analyze a complete model for scheduling in a mesh-topology multi-hop mmWave picocellular network with MU-MIMO at both transmitters and receivers. Our model characterizes the long term throughputoptimal scheduling and rate control for arbitrary MU-MIMO mesh networks using the Network Utility Maximization (NUM) framework [10], [17]. We use this model to evaluate the capacity of multi-hop mmWave picocellular mesh networks with IAB RNs under optimal scheduling.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Link Scheduling in Millimeter Wave Multi-Hop Networks With MU-MIMO Radios

Gómez-Cuba

Zorzi

2020

IEEE Trans. Wireless Commun.

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This paper studies the maximum throughput achievable with optimal scheduling in multi-hop mmWave picocellular networks with Multi-user Multiple-Input Multiple-Output (MU-MIMO) radios. MU-MIMO enables simultaneous transmission to multiple receivers (Space Division Multiplexing) and simultaneous reception from multiple transmitters (Space Division Multiple Access). The main contribution is the extension to MU-MIMO of the Network Utility Maximization (NUM) scheduling framework for multi-hop networks. We generalize to MU-MIMO the classic proof that Maximum Back Pressure (MBP) scheduling is NUM optimal. MBP requires the solution of an optimization that becomes harder with MU-MIMO radios. In prior models with one-to-one transmission and reception, each valid schedule was a matching over a graph. However, with MU-MIMO each valid schedule is, instead, a Directed Bipartite SubGraph (DBSG). In the general case this prevents finding efficient algorithms to solve the scheduler. We make MU-MIMO MBP scheduling tractable by assuming fixed power allocation, so the optimal scheduler is the Maximum Weighted DBSG. The MWDBSG problem can be solved using standard Mixed Integer Linear Programing. We simulate multi-hop mmWave picocellular networks and show that a MU-MIMO MBP scheduler enables a 160% increase in network throughput versus the classic one-to-one MBP scheduler, while fair rate allocation mechanisms are used in both cases.

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“…Baldemair et al [49] define the traffic load simply as the number of UEs per AP. Garcia-Rois et al [64] investigate scheduling on a dynamic duplex multi-hop mesh network, and also consider interference; however, the authors consider packets to be generated according to a random stochastic process. The distinguishing novelty of our paper is that multi-hop in-band millimeter-wave mesh networks are simulated and evaluated in conjunction with a realistic traffic model.…”

Section: Related Workmentioning

confidence: 99%

User level performance analysis of multi-hop in-band backhaul for 5G

2017

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In recent years, mobile access networks operating at millimeter wavelengths have received a great deal of attention, as they promise previously unattainably high mobile data rates. At these frequencies, mobile access links are expected to use highly directional beamforming antennas, which are also well suited to backhaul links. Therefore, access points can efficiently act as self-backhauled relays by using the same spectrum, circuits and antennas for mobile access and backhaul links, thus forming a multi-hop in-band backhaul network. The contributions of our paper are extensive simulations to investigate user level performance in such multi-hop networks. We specifically take into account the momentary data traffic of every link in order to calculate the interference. Results quantify the detrimental effect of interference on user level performance. Furthermore, the potential benefit of using the combination of in-band and dedicated backhaul links is evaluated. Additionally, this paper investigates the user level effects of the sudden loss of a link in the backhaul mesh network, and underlines the importance of effective rerouting algorithms. The feasibility of the inband concept is demonstrated, and we can confirm that the user level experience will surpass the performance provided by previous generation mobile networks.

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On the Analysis of Scheduling in Dynamic Duplex Multihop mmWave Cellular Systems

Cited by 55 publications

References 35 publications

5G roadmap: 10 key enabling technologies

5G roadmap: 10 key enabling technologies

Optimal Link Scheduling in Millimeter Wave Multi-Hop Networks With MU-MIMO Radios

User level performance analysis of multi-hop in-band backhaul for 5G

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