Search results for "Spectrum management"
showing 10 items of 13 documents
Error-Based Interference Detection in WiFi Networks
2017
In this paper we show that inter-technology interference can be recognized by commodity WiFi devices by monitoring the statistics of receiver errors. Indeed, while for WiFi standard frames the error probability varies during the frame reception in different frame fields (PHY, MAC headers, payloads) protected with heterogeneous coding, errors may appear randomly at any point during the time the demodulator is trying to receive an exogenous interfering signal. We thus detect and identify cross-technology interference on off-the-shelf WiFi cards by monitoring the sequence of receiver errors (bad PLCP, bad PCS, invalid headers, etc.) and develop an Artificial Neural Network (ANN) to recognize t…
Performance analysis of underlay two-way relay cooperation in cognitive radio networks with energy harvesting
2018
Abstract Cognitive radio and energy harvesting are two important approaches to solve the problem of spectrum scarcity and energy constraint in wireless communications. In this work, we study a two-way relay cooperation scheme in underlay cognitive radio networks (CRNs) with energy harvesting in which two secondary users exchange information via an energy harvesting relay node. Since the relay node collects energy from the received signals and utilizes it to forward the information, the secondary transmission power can be markedly reduced. Therefore the interference of the secondary network to the primary network can be substantially reduced. We derive the outage probability of the secondary…
Proactive Handoff of Secondary User in Cognitive Radio Network Using Machine Learning Techniques
2021
Spectrum management always appears as an essential part of modern communication systems. Handoff is initiated when the signal strength of a current user deteriorates below a certain threshold. In cognitive radio network, the perception of handoff is different due to the presence of two categories of users: certified/primary user and uncertified/secondary user. The reason for the spectrum handoff arises when the primary user (PU) returns to one of its band used by the secondary user. The spectrum handoff is of two types: reactive handoff and proactive handoff. There are certain limitations in reactive handoff, such as it suffers from prolonged handoff latency and interference. In the proacti…
Licensed and Unlicensed Spectrum Management for Energy-Efficient Cognitive M2M
2020
Edge computing has emerged as a promising solution for relieving the tension between resource-limited MTDs and computational-intensive tasks. To realize successful task offloading with limited spectrum, we focus on the cognitive machine-to-machine (CM2M) paradigm which enables a massive number of MTDs to either opportunistically use the licensed spectrum that is temporarily available, or to exploit the under-utilized unlicensed spectrum. We formulate the channel selection problem with both licensed and unlicensed spectrum as an adversarial multi-armed bandit (MAB) problem, and combine the exponential-weight algorithm for exploration and exploitation (EXP3) and Lyapunov optimization to devel…
Impact of LTE’s Periodic Interference on Heterogeneous Wi-Fi Transmissions
2018
The problem of Wi-Fi and LTE coexistence has been significantly debated in the last years, with the emergence of LTE extensions enabling the utilization of unlicensed spectrum for carrier aggregation. Rather than focusing on the problem of resource sharing between the two technologies, in this paper, we study the effects of LTE's structured transmissions on the Wi-Fi random access protocol. We show how the scheduling of periodic LTE transmissions modifies the behavior of 802.11's distributed coordination function (DCF), leading to a degradation of Wi-Fi performance, both in terms of channel utilization efficiency and in terms of channel access fairness. We also discuss the applicability and…
IEEE Access Special Section Editorial : Cloud and Big Data-Based Next-Generation Cognitive Radio Networks
2019
In cognitive radio networks (CRN), secondary users (SUs) are required to detect the presence of the licensed users, known as primary users (PUs), and to find spectrum holes for opportunistic spectrum access without causing harmful interference to PUs. However, due to complicated data processing, non-real-time information exchange and limited memory, SUs often suffer from imperfect sensing and unreliable spectrum access. Cloud computing can solve this problem by allowing the data to be stored and processed in a shared environment. Furthermore, the information from a massive number of SUs allows for more comprehensive information exchanges to assist the resource allocation and interference ma…
Enabling a win-win coexistence mechanism for WiFi and LTE in unlicensed bands
2018
The problem of WiFi and LTE coexistence has been significantly debated in the last years, with the emergence of LTE extensions enabling the utilization of unlicensed spectrum for carrier aggregation. Since the two technologies employ com-pletely different access protocols and frame transmission times, supporting coexistence with minimal modifications on existing protocols is not an easy task. Current solutions are often based on LTE unilateral adaptations, being LTE in unlicensed bands still under definition. In this paper, we demonstrate that it is possible to avoid a subordinated role for WiFi nodes, by simply equipping WiFi nodes with a sensing mechanism based on adaptive tunings of the …
Secondary users selection and sparse narrow-band interference mitigation in cognitive radio networks
2018
Spectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and services. To address this problem, different spectrum management techniques have been proposed in the literature such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with the licensed users. The main challenges in overlay CR networks are the identification and detection of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore, in this paper, we investigate the performance of an orthogonal frequency division multiplexing (OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. …
Energy Harvesting Enabled Energy Efficient Cognitive Machine-to-Machine Communications
2020
Energy harvesting based cognitive machine-to-machine (EH-CM2M) communication has been introduced to overcome the problem of spectrum scarcity and limited battery capacity by enabling M2M transmitters (M2M-TXs) to harvest energy from ambient radio frequency signals, as well as to reuse the resource blocks (RBs) allocated to CUs in an opportunistic manner. However, the complex interference scenarios and the stringent QoS requirements pose new challenges on resource allocation optimization. In this chapter, we consider how to maximize the energy efficiency of M2M-TXs via the joint optimization of channel selection, peer discovery, power control, and time allocation.
Learning From Errors: Detecting Cross-Technology Interference in WiFi Networks
2018
In this paper, we show that inter-technology interference can be recognized using commodity WiFi devices by monitoring the statistics of receiver errors. Indeed, while for WiFi standard frames the error probability varies during the frame reception in different frame fields (PHY, MAC headers, and payloads) protected with heterogeneous coding, errors may appear randomly at any point during the time the demodulator is trying to receive an exogenous interfering signal. We thus detect and identify cross-technology interference on off-the-shelf WiFi cards by monitoring the sequence of receiver errors (bad PLCP, bad FCS, invalid headers, etc.) and propose two methods to recognize the source of in…