Learning-based Resource Allocation for Backscatter-aided Vehicular Networks

This work sheds light on a novel learning-based optimization framework for heterogeneous backscatter vehicular networks. More specifically, the article presents a resource allocation and user association scheme for large-scale heterogeneous backscatter vehicular networks by considering a collaboration centric spectrum sharing mechanism. In the considered network setup, multiple network service providers (NSPs) own the resources to serve several legacy and backscatter vehicular users in the network. For each NSP, the legacy vehicle user operates under the macro cell, whereas, the backscatter vehicle user operates under small private cells using leased spectrum resources. A joint power allocation, user association, and spectrum sharing problem has been formulated with an objective to maximize the utility of NSPs. In order to overcome challenges of high dimensionality and non-convexity, the problem is divided into two subproblems. Subsequently, a reinforcement learning and a supervised deep learning approach have been used to solve both subproblems in an efficient and effective manner.

Learning-based Resource Allocation for Backscatter-aided Vehicular Networks

This work sheds light on a novel learning-based optimization framework for heterogeneous backscatter vehicular networks. More specifically, the article presents a resource allocation and user association scheme for large-scale heterogeneous backscatter vehicular networks by considering a collaboration centric spectrum sharing mechanism. In the considered network setup, multiple network service providers (NSPs) own the resources to serve several legacy and backscatter vehicular users in the network. For each NSP, the legacy vehicle user operates under the macro cell, whereas, the backscatter vehicle user operates under small private cells using leased spectrum resources. A joint power allocation, user association, and spectrum sharing problem has been formulated with an objective to maximize the utility of NSPs. In order to overcome challenges of high dimensionality and non-convexity, the problem is divided into two subproblems. Subsequently, a reinforcement learning and a supervised deep learning approach have been used to solve both subproblems in an efficient and effective manner.

Performance measurement of small-cells deployed under a heterogeneous network: an analysis of the co-existence of small-cells with the macro‑cell in 5G NR

Advancements of cellular networks such as 4G and 5G proposed the collaboration of small-cell technologies in mobile networks and constructed a heterogeneous network (HetNet) for collaborative connectivity. There are many benefits of small-cell-based collective communication such as the increase of device capability in indoor/outdoor locations, enhancement of wireless coverage, improved signal efficiency, lower implementation costs of gNB (Next-generation Base Station introduced in 5G), etc. The integration of small-cells by deploying low-power BSs (base stations) in conventional macro-gNBs was investigated as a convenient and economical way of raising the potentials of a cellular network with high demand from consumers. The fusion of small-cells with macro-cells offers increased coverage and capacity for heterogeneous networks. Therefore, the research aimed to realize the performance of a small-cell deployed under a macro-cell in a two-tier heterogeneous network. The research first modified the reference equation for measuring the received power by introducing the transmitter and receiver gain. The paper then measured the SINR, throughput, spectral efficiency, and power efficiency for both downlink and uplink by empirical simulation. The research further enlisted the notable outcomes after examining the simulation results and discussed some relevant research scopes in the concluding sections of the paper.

Perencanaan LTE-A untuk Heterogeneous Network dengan Metode CADS4 di Grand Asia Afrika

ABSTRAKBerdasarkan hasil pengukuran di Grand Asia Afrika (GAA) diketahui terdapat peningkatan kualitas jaringan setelah pemasangan unit COMBAT selama 7 hari. RSRP ≥ -95 dBm sebelumnya sebesar 75,70% menjadi 100%, SINR ≥ 0 dB dari 53,58% menjadi 97,54%, dan throughput ≥ 8 Mbps sebelumnya sebesar 48,12% menjadi 89,55%. Untuk mempertahankan kualitas tersebut maka dibangunlah small cell. Perencanaan menerapkan metode inter-band carrier aggregation pada heterogen network LTE dengan skema CADS4 sebagai pengganti unit COMBAT. Tujuan perencanaan ini adalah extended throughput dan agar kualitas layanan pada beban trafik tinggi tetap baik. Macro cell sebagai Primary Cell (PCell) pada band-1 2100 MHz dan micro cell sebagai Secondary Cell (SCell) pada band-3 1800 MHz. Hasil perencanaan menunjukkan telah memenuhi standar RF Parameter LTE yaitu RSRP sebesar -92,65 dBm, SINR sebesar 16,55 dB, throughput sebesar 1,062 Mbps, dan user connected 97%.Kata kunci: LTE-A, heterogen network, CADS4, Great Asia Afrika Bandung ABSTRACTBased on the report on the development of temporary sites in the tourist area of Great Asia Africa (GAA), it shows that the DRR rate is> 90% in the sectors leading to GAA. From the measurement, it is known that there is an increase in network quality after installing the COMBAT unit for 7 days. For RSRP ≥ -95 dBm, the previous amount was 75.70% to 100.00%, for SINR ≥ 0 dB previously it was 53.58% to 97.54%, and for throughput ≥ 8 Mbps the previous was 48.12% to 89,55%. To maintain the quality of the network, small cells were built to cover the GAA area. Planning to apply the inter-band carrier aggregation method to the heterogeneous LTE network with the CADS4 scheme to replace the COMBAT unit. The purpose of planning is to provide extended throughput and so that the service quality at high traffic loads remains good. The configuration used is a macro cell as a Primary Cell (PCell) in the band-1 2100 MHz and a micro cell as a Secondry Cell (SCell) in the 1800 MHz band-3. The results of the planning meet the LTE parameter RF standards, RSRP of -92.65 dBm, SINR of 16.55 dB, throughput of 1.062 Mbps, and users connected to 97%.Keywords: LTE-A, heterogen network, CADS4, Great Asia Afrika Bandung