BRNN-LSTM for Initial Access in Millimeter Wave Communications

Fog-radio access networks (F-RANs) alleviate fronthaul delays for cellular networks as compared to their cloud counterparts. This allows them to be suitable solutions for networks that demand low propagation delays. Namely, they are suitable for millimeter wave (mmWave) operations that suffer from short propagation distances and possess a poor scattering environment (low channel ranks). The F-RAN here is comprised of fog nodes that are collocated with radio remote heads (RRHs) to provide local processing capabilities for mobile station (MS) terminals. These terminals demand various network functions (NFs) that correspond to different service requests. Now, provisioning these NFs on the fog nodes also yields service delays due to the requirement for service migration from the cloud, i.e., offloading to the fog nodes. One solution to reduce this service delay is to provide cached copies of popular NFs in advance. Hence, it is critical to study function popularity and allow for content caching at the F-RAN. This is further a necessity given the limited resources at the fog nodes, thus requiring efficient resource management to enhance network capacity at reduced power and cost penalty. This paper proposes novel solutions that allocate popular NFs on the fog nodes to accelerate services for the terminals, namely, the clustered and distributed caching methods. The two methods are analyzed and compared against the baseline uncached provisioning schemes in terms of service delay, energy consumption, and cost.

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“…In general, the poor scattering propagation nature at mmWave bands imposes the use of geometric channel models, written as [30,31],…”

Section: Downlink Modelmentioning

confidence: 99%

“…where the variables P tr and C MS denote the transmitted signal power and the MS combiner, respectively, and where C MS includes baseband and analog combiners, such that In general, the poor scattering propagation nature at mmWav use of geometric channel models, written as [30,31],…”

Section: Cache Modelmentioning

confidence: 99%

Clustered and Distributed Caching Methods for F-RAN-Based mmWave Communications

et al. 2022

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“…Iterative search operates a two-phase scanning of the angular space [24]. The scanning direction is established using a predetermined codebook [25]. In the first phase, the BS conducts an exhaustive search through different sectors in a sequential manner.…”

Section: ) Iterative Searchmentioning

confidence: 99%

Initial Access & Beam Alignment for mmWave and Terahertz Communications

2022

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The initial access in Millimeter wave (mmWave) 5G communications is very challenging and time consuming. In general, mmWave and terahertz communications require the use of directional antennas to seek narrow beams. However, due to this directionality, many issues can impact the beam alignment between transmitter and receiver. In this paper, we present a comprehensive survey of beam alignment and initial access in mmWave and terahertz 5G/6G systems. First, we present a detailed overview of initial access methods, techniques, and beam management procedures. Then, we classify recent works related to beam alignment based on their objective functions (i.e., latency, power allocation, QoS, energy consumption, cost). We also highlight the beam alignment in terahertz 6G, where we find that deep learning and reconfigurable intelligent surface are the two protagonists that help to achieve fast beam alignment.INDEX TERMS 5G/6G, mmWave, terahertz, beamforming, initial access, beam alignment, beam steering, reconfigurable intelligent surface.

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“…The network can predict the content popularity of the incoming NFs using machine learning algorithms. Hence, this work considers the prediction outcomes of the long short‐term memory algorithm in Aldalbahi et al 23,24 in the caching model. These popular NFs are shown in Figure 2, which is taken from the study in Aldalbahi et al, 23 where the NF

f_{1}

represents the call‐in,

f_{2}

represents the call‐out,

f_{3}

accounts for the sms‐in,

f_{4}

accounts for the sms‐out, and

f_{5}

represents the internet traffic.…”

Section: System Modelmentioning

confidence: 99%

Caching of popular content at F‐RAN for mmWave new radio

Aldalbahi

Jasim

Bouzguenda

et al. 2022

Int J Communication

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Summary Fog computing allows for local data processing at the edge of the network. This allows for reduced link delays between mobile users and access points. Here, fog nodes are collocated with radio remote heads (RRHs) to provide local processing capabilities, that is, creating fog radio access network (F‐RAN) that can support ultralow latency for cellular networks that operate on millimeter wave (mmWave) bands. Here, mobile stations (MS) demand various network functions (NFs) that correspond to different service requests. Hence, it is critical to study function popularity and allow content caching at the F‐RAN. Given the limited resources at the fog nodes, it is important to efficiently manage the resources to improve network operations and enhance the capacity at reduced delays and cost. Therefore, caching in mmWave F‐RAN requires node allocation that can accommodate the highest number of cached functions. Hence, this paper proposes a novel node placement scheme that leverages Nelder–Mead meta‐heuristic. Results show that the proposed scheme yields in reduced delay, cost, and power and energy consumption.

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BRNN-LSTM for Initial Access in Millimeter Wave Communications

Cited by 12 publications

References 19 publications

Clustered and Distributed Caching Methods for F-RAN-Based mmWave Communications

Clustered and Distributed Caching Methods for F-RAN-Based mmWave Communications

Initial Access & Beam Alignment for mmWave and Terahertz Communications

Caching of popular content at F‐RAN for mmWave new radio

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