Load-aware modeling for uplink cellular networks in a multi-channel environment

AlAmmouri, Ahmad; ElSawy, Hesham; Alouini, Mohamed‐Slim

doi:10.1109/pimrc.2014.7136422

Cited by 19 publications

(35 citation statements)

References 10 publications

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“…It is assumed that the BSs are dense enough such that each of the CHs can invert its path-loss towards the closest BS almost surely, and hence the maximum transmit power of the IoT devices is not a binding constraint for packet transmission. Extension to fractional power control and/or adding a maximum power constraint can be done by following the methodologies in [29] and [30]. An RA transmission is assumed to be decodable if the signal to interference and noise ratio (SINR), denoted by Υ RA , is greater than a certain threshold θ RA .…”

Section: B Random Access Over the Lte Networkmentioning

confidence: 99%

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Self-Organized Scheduling Request for Uplink 5G Networks: A D2D Clustering Approach

Gharbieh

Bader²,

ElSawy

et al. 2019

IEEE Trans. Commun.

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In one of the several manifestations, the future cellular networks are required to accommodate a massive number of devices; several orders of magnitude compared to today's networks. At the same time, the future cellular networks will have to fulfill stringent latency constraints. To that end, one problem that is posed as a potential showstopper is extreme congestion for requesting uplink scheduling over the physical random access channel (PRACH). Indeed, such congestion drags along scheduling delay problems. In this paper, the use of self-organized device-to-device (D2D) clustering is advocated for mitigating PRACH congestion. To this end, the paper proposes two D2D clustering schemes, namely; Random-Based Clustering (RBC) and Channel-Gain-Based Clustering (CGBC). Accordingly, this paper sheds light on random access within the proposed D2D clustering schemes and presents a case study based on a stochastic geometry framework. For the sake of objective evaluation, the D2D clustering is benchmarked by the conventional scheduling request procedure. Accordingly, the paper offers insights into useful scenarios that minimize the scheduling delay for each clustering scheme. Finally, the paper discusses the implementation algorithm and some potential implementation issues and remedies.

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Section: B Random Access Over the Lte Networkmentioning

confidence: 99%

“…The constraint of scheduling one CM per Voronoi cell of the cluster leads to a Voronoiperturbed point process for the set of mutually interfering CMs. Approximation 2 is commonly used in the literature to maintain tractability [29], [30], [34]- [38]. Remark 3.…”

Section: Approximation 2 For the D2d Transmission The Point Processmentioning

confidence: 99%

Self-Organized Scheduling Request for Uplink 5G Networks: A D2D Clustering Approach

Gharbieh

Bader²,

ElSawy

et al. 2019

IEEE Trans. Commun.

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“…It is assumed the BSs are dense enough such that each of the devices can invert its path loss towards the closest BS almost surely, so the maximum transmit power of the UEs is not a binding constraint for the RACH access. Extension to RACH access with fractional power control and adding a maximum power constraint can be done by following the methodologies in [9] and [10], respectively. Upon RACH access failure, the ZC code selection is repeated and the device follow one of the following three schemes:…”

Section: B Rach Access Schemementioning

confidence: 99%

Tractable Stochastic Geometry Model for IoT Access in LTE Networks

Gharbieh

ElSawy

Bader

et al. 2016

2016 IEEE Global Communications Conference (GLOBECOM)

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The Internet of Things (IoT) is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the high volumes of traffic that must be accommodated. Cellular networks are indeed a natural candidate for the data tsunami the IoT is expected to generate in conjunction with legacy human-type traffic. However, the random access process for scheduling request represents a major bottleneck to support IoT via LTE cellular networks. Accordingly, this paper develops a mathematical framework to model and study the random access channel (RACH) scalability to accommodate IoT traffic. The developed model is based on stochastic geometry and discrete time Markov chains (DTMC) to account for different access strategies and possible sources of inter-cell and intra-cell interferences. To this end, the developed model is utilized to assess and compare three different access strategies, which incorporate a combination of transmission persistency, back-off, and power ramping. The analysis and the results showcased herewith clearly illustrate the vulnerability of the random access procedure as the IoT intensity grows. Finally, the paper offers insights into effective scenarios for each transmission strategy in terms of IoT intensity and RACH detection thresholds.

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“…α-Duplex Model Universal frequency reuse is adopted with no intra-cell interference. Hence, only one UE per BS is active at a given 2 Truncation outage and the effect of allowing UEs in truncation to transmit with the maximum transmit power has been studied in [7], [12] and are out of the scope of the current paper. frequency channel.…”

Section: A Network Modelmentioning

confidence: 99%

“…Let the LT of the RV variable y in this case be donated by L I d (z), then using (12), the BER in the downlink direction is given by,…”

Section: Performance Analysismentioning

confidence: 99%

In-Band Full-Duplex Communications for Cellular Networks with Partial Uplink/Downlink Overlap

AlAmmouri

ElSawy

Amin

et al. 2015

2015 IEEE Global Communications Conference (GLOBECOM)

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Load-aware modeling for uplink cellular networks in a multi-channel environment

Cited by 19 publications

References 10 publications

Self-Organized Scheduling Request for Uplink 5G Networks: A D2D Clustering Approach

Self-Organized Scheduling Request for Uplink 5G Networks: A D2D Clustering Approach

Tractable Stochastic Geometry Model for IoT Access in LTE Networks

In-Band Full-Duplex Communications for Cellular Networks with Partial Uplink/Downlink Overlap

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