1,781 research outputs found
Performance analyses and design for cognitive radios
Cognitive radio has been proposed as a promising solution to the conflict between
the spectrum scarcity and spectrum under-utilization. As the demand increases for
wireless communication services, cognitive radio technology attracts huge attention
from both commercial industries and academic researches. The purpose of this thesis
is to provide an analytical evaluation of the cognitive radio system performance
while taking into consideration of some realistic conditions. Several problems are
investigated in this thesis. First, by adopting a dynamic primary user traffic model
with one primary user occupancy status change and exponentially distributed channel
holding times, its effect on the cognitive radio system performance is evaluated.
In the evaluation, the sensing-throughput tradeoff of the cognitive radio is used
as the examination criteria, while energy detection is applied during the spectrum
sensing. The thesis then takes the investigation further by establishing a primary
user multiple changes traffic model which considers multiple primary user occupancy
status changes and any reasonable channel holding time distributions. The effect of
the primary user multiple changes traffic on the spectrum sensing performance is investigated
while the channel holding times are assumed to be exponential, Gamma,
Erlang and log-normal distributed. The analytical evaluation of cognitive radio is
also carried out from the secondary user transmission perspective, where the performance of the adaptive modulation in cognitive radio system is investigated. The
effect of the cognitive radio distinctive features on the performance of both the adaptive
continuous rate scheme and the adaptive discrete rate scheme of the adaptive
modulation are examined. The BER performance and the link spectral efficiency
performance are derived for both schemes.
A novel frame structure where the spectrum sensing is performed by using the
recovered received secondary frames is also evaluated in this thesis. A realistic
scenario which considers the secondary user signal decoding errors is examined for
the novel structure, while an ideal upper bound performance is given when the
decoding process is assumed perfect. By extending the system to include multiple
consecutive secondary frames, the performance of the novel structure is compared
to the performance of the traditional frame structure proposed by the IEEE 802.22
WRAN standard. The effect of the primary user multiple changes traffic is also
examined for the novel structure.
Several major findings are made from the analytical evaluations presented in
this thesis. Through numerical examinations, it was shown that, first, the dynamic
primary user traffic degrades the performance of cognitive radio systems. Second,
the degree of the performance degradation of the cognitive radio systems is related
to the number of primary user status changes and the primary user traffic intensity.
Different primary user channel holding times distributions also lead to different
sensitivities of the system performance to the primary user traffic. Third, cognitive
radio distinctive features degrades the performance of the adaptive modulation.
When the novel structure is applied for cognitive radio, a higher secondary achievable
throughput can be obtained with a limited saturation threshold
Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks
Cognitive radio has been widely considered as one of the prominent solutions
to tackle the spectrum scarcity. While the majority of existing research has
focused on single-band cognitive radio, multiband cognitive radio represents
great promises towards implementing efficient cognitive networks compared to
single-based networks. Multiband cognitive radio networks (MB-CRNs) are
expected to significantly enhance the network's throughput and provide better
channel maintenance by reducing handoff frequency. Nevertheless, the wideband
front-end and the multiband spectrum access impose a number of challenges yet
to overcome. This paper provides an in-depth analysis on the recent
advancements in multiband spectrum sensing techniques, their limitations, and
possible future directions to improve them. We study cooperative communications
for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also
investigate several limits and tradeoffs of various design parameters for
MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that
differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE
Journal, Special Issue on Future Radio Spectrum Access, March 201
Compressed Sensing based Low-Power Multi-View Video Coding and Transmission in Wireless Multi-Path Multi-Hop Networks
Wireless Multimedia Sensor Network (WMSN) is increasingly being deployed for surveillance, monitoring and Internet-of-Things (IoT) sensing applications where a set of cameras capture and compress local images and then transmit the data to a remote controller. Such captured local images may also be compressed in a multi-view fashion to reduce the redundancy among overlapping views. In this paper, we present a novel paradigm for compressed-sensing-enabled multi-view coding and streaming in WMSN. We first propose a new encoding and decoding architecture for multi-view video systems based on Compressed Sensing (CS) principles, composed of cooperative sparsity-aware block-level rate-adaptive encoders, feedback channels and independent decoders. The proposed architecture leverages the properties of CS to overcome many limitations of traditional encoding techniques, specifically massive storage requirements and high computational complexity. Then, we present a modeling framework that exploits the aforementioned coding architecture. The proposed mathematical problem minimizes the power consumption by jointly determining the encoding rate and multi-path rate allocation subject to distortion and energy constraints. Extensive performance evaluation results show that the proposed framework is able to transmit multi-view streams with guaranteed video quality at lower power consumption
Multiple Access for Massive Machine Type Communications
The internet we have known thus far has been an internet of people, as it has connected people with one another. However, these connections are forecasted to occupy only a minuscule of future communications. The internet of tomorrow is indeed: the internet of things. The Internet of Things (IoT) promises to improve all aspects of life by connecting everything to everything. An enormous amount of effort is being exerted to turn these visions into a reality. Sensors and actuators will communicate and operate in an automated fashion with no or minimal human intervention. In the current literature, these sensors and actuators are referred to as machines, and the communication amongst these machines is referred to as Machine to Machine (M2M) communication or Machine-Type Communication (MTC). As IoT requires a seamless mode of communication that is available anywhere and anytime, wireless communications will be one of the key enabling technologies for IoT. In existing wireless cellular networks, users with data to transmit first need to request channel access. All access requests are processed by a central unit that in return either grants or denies the access request. Once granted access, users' data transmissions are non-overlapping and interference free. However, as the number of IoT devices is forecasted to be in the order of hundreds of millions, if not billions, in the near future, the access channels of existing cellular networks are predicted to suffer from severe congestion and, thus, incur unpredictable latencies in the system. On the other hand, in random access, users with data to transmit will access the channel in an uncoordinated and probabilistic fashion, thus, requiring little or no signalling overhead. However, this reduction in overhead is at the expense of reliability and efficiency due to the interference caused by contending users. In most existing random access schemes, packets are lost when they experience interference from other packets transmitted over the same resources. Moreover, most existing random access schemes are best-effort schemes with almost no Quality of Service (QoS) guarantees. In this thesis, we investigate the performance of different random access schemes in different settings to resolve the problem of the massive access of IoT devices with diverse QoS guarantees. First, we take a step towards re-designing existing random access protocols such that they are more practical and more efficient. For many years, researchers have adopted the collision channel model in random access schemes: a collision is the event of two or more users transmitting over the same time-frequency resources. In the event of a collision, all the involved data is lost, and users need to retransmit their information. However, in practice, data can be recovered even in the presence of interference provided that the power of the signal is sufficiently larger than the power of the noise and the power of the interference. Based on this, we re-define the event of collision as the event of the interference power exceeding a pre-determined threshold. We propose a new analytical framework to compute the probability of packet recovery failure inspired by error control codes on graph. We optimize the random access parameters based on evolution strategies. Our results show a significant improvement in performance in terms of reliability and efficiency. Next, we focus on supporting the heterogeneous IoT applications and accommodating their diverse latency and reliability requirements in a unified access scheme. We propose a multi-stage approach where each group of applications transmits in different stages with different probabilities. We propose a new analytical framework to compute the probability of packet recovery failure for each group in each stage. We also optimize the random access parameters using evolution strategies. Our results show that our proposed scheme can outperform coordinated access schemes of existing cellular networks when the number of users is very large. Finally, we investigate random non-orthogonal multiple access schemes that are known to achieve a higher spectrum efficiency and are known to support higher loads. In our proposed scheme, user detection and channel estimation are carried out via pilot sequences that are transmitted simultaneously with the user's data. Here, a collision event is defined as the event of two or more users selecting the same pilot sequence. All collisions are regarded as interference to the remaining users. We first study the distribution of the interference power and derive its expression. Then, we use this expression to derive simple yet accurate analytical bounds on the throughput and outage probability of the proposed scheme. We consider both joint decoding as well as successive interference cancellation. We show that the proposed scheme is especially useful in the case of short packet transmission
Spectrum Monitoring Algorithms for Wireless and Satellite Communications
Nowadays, there is an increasing demand for more efficient utilization of the radio frequency
spectrum as new terrestrial and space services are deployed resulting in the
congestion of the already crowded frequency bands. In this context, spectrum monitoring
is a necessity. Spectrum monitoring techniques can be applied in a cognitive radio
network, exploiting the spectrum holes and allowing the secondary users to have access
in an unlicensed frequency band for them, when it is not occupied by the primary user.
Furthermore, spectrum monitoring techniques can be used for interference detection in
wireless and satellite communications. These two topics are addressed in this thesis.
In the beginning, a detailed survey of the existing spectrum monitoring techniques according
to the way that cognitive radio users 1) can detect the presence or absence of
the primary user; and 2) can access the licensed spectrum is provided. Subsequently, an
overview of the problem of satellite interference and existing methods for its detection
are discussed, while the contributions of this thesis are presented as well.
Moreover, this thesis discusses some issues in a cognitive radio system such as the reduction
of the secondary user's throughput of the conventional \listen before talk" access
method in the spectrum. Then, the idea of simultaneous spectrum sensing and data
transmission through the collaboration of the secondary transmitter with receiver is
proposed to address these concerns. First, the secondary receiver decodes the signal
from the secondary transmitter, then, removes it from the total received signal and finally, applies spectrum sensing in the remaining signal in order to decide if the primary
user is active or idle. The effects of the imperfect signal cancellation due to decoding
errors, which are ignored in the existing literature, are considered in our analysis. The
analytical expressions for the probabilities of false alarm and detection are derived and
numerical results through simulations are also presented to validate the proposed study.
Furthermore, the threat of interference for the satellite communications services is studied
in this thesis. It proposes the detection of interference on-board the satellite by
introducing a spectrum monitoring unit within the satellite transponder. This development
will bring several benefits such as faster reaction time and simplification of the
ground stations in multi-beam satellite systems. Then, two algorithms for the detection
of interference are provided. The first detection scheme is based on energy detector with
signal cancellation exploiting the pilot symbols. The second detection scheme considers
a two-stage detector, where first, the energy detector with signal cancellation in the pilot
domain is performed, and if required, an energy detector with signal cancellation in the
data domain is carried out in the second stage. Moreover, the analytical expressions for the probabilities of false alarm and detection are derived and numerical results through
simulations are provided to verify the accuracy of the proposed analysis.
Finally, this thesis goes one step further and the developed algorithms are evaluated
experimentally using software defined radios, particularly universal software radio peripherals
(USRPs), while it concludes discussing some open research topics
Partial OFDM Symbol Recovery to Improve Interfering Wireless Networks Operation in Collision Environments
The uplink data rate region for interfering transmissions in wireless networks has been characterised and proven, yet its underlying model assumes a complete temporal overlap. Practical unplanned networks, however, adopt packetized transmissions and eschew tight inter-network coordination, resulting in packet collisions that often partially overlap, but rarely ever completely overlap. In this work, we report a new design called (), that specifically targets the parts of data symbols that experience no interference during a packet collision. bootstraps a successive interference cancellation (SIC) like decoder from these strong signals, thus improving performance over techniques oblivious to such partial packet overlaps. We have implemented on the WARP software-defined radio platform and in trace-based simulation. Our performance evaluation presents experimental results from this implementation operating in a 12node software network testbed, spread over two rooms in a nonlineofsight indoor office environment. Experimental results confirm that our proposal decoder is capable of decoding up to 60 % of collided frames depending on the type of data and modulation used. This consistently leads to throughput enhancement over conventional WiFi under different scenarios and for the various data types tested, namely downlink bulk TCP, downlink videoondemand, and uplink UDP
Versatility Of Low-Power Wide-Area Network Applications
Low-Power Wide-Area Network (LPWAN) is regarded as the leading communication technology for wide-area Internet-of-Things (IoT) applications. It offers low-power, long-range, and low-cost communication. With different communication requirements for varying IoT applications, many competing LPWAN technologies operating in both licensed (e.g., NB-IoT, LTE-M, and 5G) and unlicensed (e.g., LoRa and SigFox) bands have emerged. LPWANs are designed to support applications with low-power and low data rate operations. They are not well-designed to host applications that involve high mobility, high traffic, or real-time communication (e.g., volcano monitoring and control applications).With the increasing number of mobile devices in many IoT domains (e.g., agricultural IoT and smart city), mobility support is not well-addressed in LPWAN. Cellular-based/licensed LPWAN relies on the wired infrastructure to enable mobility. On the other hand, most unlicensed LPWANs operate on the crowded ISM band or are required to duty cycle, making handling mobility a challenge.
In this dissertation, we first identify the key opportunities of LPWAN, highlight the challenges, and show potential directions for future research. We then enable the versatility of LPWAN applications first by enabling applications involving mobility over LPWAN. Specifically, we propose to handle mobility in LPWAN over white space considering Sensor Network Over White Space (SNOW). SNOW is a highly scalable and energy-efficient LPWAN operating over the TV white spaces. TV white spaces are the allocated but locally unused available TV channels (54 - 698 MHz in the US). We proposed a dynamic Carrier Frequency Offset (CFO) estimation and compensation technique that considers the impact of the Doppler shift due to mobility. Also, we design energy-efficient and fast BS discovery and association approaches. Finally, we demonstrate the feasibility of our approach through experiments in different deployments.
Finally, we present a collision detection and recovery technique called RnR (Reverse & Replace Decoding) that applies to LPWANs. Additionally, we discuss future work to enable handling burst transmission over LPWAN and localization in mobile LPWAN
EXTRINSIC CHANNEL-LIKE FINGERPRINT EMBEDDING FOR TRANSMITTER AUTHENTICATION IN WIRELESS SYSTEMS
We present a physical-layer fingerprint-embedding scheme for wireless signals, focusing on multiple input multiple output (MIMO) and orthogonal frequency division multiplexing (OFDM) transmissions, where the fingerprint signal conveys a low capacity communication suitable for authenticating the transmission and further facilitating secure communications. Our system strives to embed the fingerprint message into the noise subspace of the channel estimates obtained by the receiver, using a number of signal spreading techniques. When side information of channel state is known and leveraged by the transmitter, the performance of the fingerprint embedding can be improved. When channel state information is not known, blind spreading techniques are applied. The fingerprint message is only visible to aware receivers who explicitly preform detection of the signal, but is invisible to receivers employing typical channel equalization. A taxonomy of overlay designs is discussed and these designs are explored through experiment using time-varying channel-state information (CSI) recorded from IEEE802.16e Mobile WiMax base stations. The performance of the fingerprint signal as received by a WiMax subscriber is demonstrated using CSI measurements derived from the downlink signal. Detection performance for the digital fingerprint message in time-varying channel conditions is also presented via simulation
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