A Baseband Wireless Spectrum Hypervisor for Multiplexing Concurrent OFDM Signals

Abstract

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.

Performance evaluation of wireless local area network with congested fading channels

“…The experimental mm-Wave and Wi-Fi network is configured as described in 4 where the multi-baseband-client at destination possesses an IEEE 802.11ay radio. The multi-baseband access point (MBAP) [22] can communicate through 60 GHz links. The MBAP and clients are observing the MPFC.…”

Physical Wireless Resource Virtualization for Software-Defined Whole-Stack Slicing

“…More specifically, we verify how the inter-domain I/Q sample streaming scales with respect to the number of OAI slices for different LTE bandwidths. In addition, the Wireless Spectrum Hypervisor [20] uses a ZMQ socket with the PUB-SUB (Publish-Subscribe) pattern for I/Q sample streaming. Therefore, we also compare the PV-RAN method of sharedmemory inter-domain I/Q sample streaming against the ZMQ PUB-SUB I/Q sample streaming method.…”

“…The aforementioned studies have touched on various aspects of RAN virtualization, but they have not considered virtualizing the physical wireless resources for whole-stack slicing. The work closest to PV-RAN is that of the Wireless Spectrum Hypervisor [20]. It considered multiplexing several OFDM signal streams through a shared SDR.…”

F-OFDM in a novel form for analyzing 5G networks

“…As a result, filtered alerts have been widely seen as long overdue in order to certify the waveform of 5G structures. This is owing to the ability to provide asynchronous transmission using filtered waveforms, which decreases OOB emission, recommends filter-based waveforms, and outperforms OFDM [34][35][36][37].…”