Multi-Beam Multi-Stream Communications for 5G and beyond Mobile User Equipment and UAV Proof of Concept Designs

Huo, Yiming; Lu, Franklin; Wu, Felix; Dong, Xiaodai

doi:10.1109/vtcfall.2019.8891154

Cited by 29 publications

(13 citation statements)

References 20 publications

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“…As can be seen by inspecting (6), out of N subcarriers/bins, only the lower and upper N vPHY 2 bins contain useful values, i.e., values different from zero. We consider in (6) that the filters have a perfect window-shaped frequency response, which is not true in practice but can be approximated by well-designed high order low-pass filters [19].…”

Section: Multiplexing Concurrent Ofdm Signalsmentioning

confidence: 99%

“…... Next, the wide baseband representation of the k-th narrow sub-band signal, y r k wBB (n), is subject to a down-sampling operation, as depicted in Figure 5, in order to have a narrow baseband representation of the sub-band signal, which can then be fed into a PHY for data decoding. After down-sampling, the signal expressed by (6), can be written as…”

Section: Multiplexing Concurrent Ofdm Signalsmentioning

confidence: 99%

“…The research and development of future mobile networks (i.e., next generation mobile networks) has been derived by several novel breakthroughs in a myriad of areas. The recent advancements of technologies such as licensed assisted access, carrier aggregation, massive multiple-input-multiple-output (massive MIMO), cooperative spectrum sensing, beamforming techniques, compressive sensing, machine learning, etc., have provided exciting and encouraging approaches to address the forecast increase in number of connections and their respective speeds [3][4][5][6][7]. These demanding requirements pose daunting challenges to the design of both base stations and user equipment.…”

Section: Introductionmentioning

confidence: 99%

“…These demanding requirements pose daunting challenges to the design of both base stations and user equipment. In particular, at the user equipment side, these new requirements bring a series of daring implementation issues due to limited design budget and hardware resources imposed to the implementation of those devices [6,8].…”

Section: Introductionmentioning

confidence: 99%

“…To support the expected growth in capacity, the forecast for the future mobile networks, the area throughput, i.e., bit/s/km 2 , needs to be increased. Some ways to improve area throughput in cellular networks include densification of existing cellular networks using extra-small cells, provision of peer-to-peer (P2P) communications, multi-tier heterogeneous networks, full-duplex communication, massive MIMO, millimeter-wave technologies, cognitive radios, beam division multiple access (BDMA), cloud-based radio access networks (CRAN) and wireless networks virtualization (WNV) [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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A Baseband Wireless Spectrum Hypervisor for Multiplexing Concurrent OFDM Signals

Figueiredo

Mennes

Jabandzic

et al. 2020

Sensors

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The next generation of wireless and mobile networks will have to handle a significant increase in traffic load compared to the current ones. This situation calls for novel ways to increase the spectral efficiency. Therefore, in this paper, we propose a wireless spectrum hypervisor architecture that abstracts a radio frequency (RF) front-end into a configurable number of virtual RF front ends. The proposed architecture has the ability to enable flexible spectrum access in existing wireless and mobile networks, which is a challenging task due to the limited spectrum programmability, i.e., the capability a system has to change the spectral properties of a given signal to fit an arbitrary frequency allocation. The proposed architecture is a non-intrusive and highly optimized wireless hypervisor that multiplexes the signals of several different and concurrent multi-carrier-based radio access technologies with numerologies that are multiple integers of one another, which are also referred in our work as radio access technologies with correlated numerology. For example, the proposed architecture can multiplex the signals of several Wi-Fi access points, several LTE base stations, several WiMAX base stations, etc. As it able to multiplex the signals of radio access technologies with correlated numerology, it can, for instance, multiplex the signals of LTE, 5G-NR and NB-IoT base stations. It abstracts a radio frequency front-end into a configurable number of virtual RF front ends, making it possible for such different technologies to share the same RF front-end and consequently reduce the costs and increasing the spectral efficiency by employing densification, once several networks share the same infrastructure or by dynamically accessing free chunks of spectrum. Therefore, the main goal of the proposed approach is to improve spectral efficiency by efficiently using vacant gaps in congested spectrum bandwidths or adopting network densification through infrastructure sharing. We demonstrate mathematically how our proposed approach works and present several simulation results proving its functionality and efficiency. Additionally, we designed and implemented an open-source and free proof of concept prototype of the proposed architecture, which can be used by researchers and developers to run experiments or extend the concept to other applications. We present several experimental results used to validate the proposed prototype. We demonstrate that the prototype can easily handle up to 12 concurrent physical layers.

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Section: Multiplexing Concurrent Ofdm Signalsmentioning

confidence: 99%

Section: Multiplexing Concurrent Ofdm Signalsmentioning

confidence: 99%