Filter Bank Multicarrier Modulation for Spectrally Agile Waveform Design

In recent years the demand for spectrum has been steadily growing. With the limited amount of spectrum available, Spectrum Pooling has gained immense popularity. As a result of various studies, it has been established that most of the licensed spectrum remains underutilized. Spectrum Pooling or spectrum sharing concentrates on making the most of these whitespaces in the licensed spectrum. These unused parts of the spectrum are usually available in chunks. A secondary user looking to utilize these chunks needs a device capable of transmitting over distributed frequencies, while not interfering with the primary user. Such a process is known as Dynamic Spectrum Access (DSA) and a device capable of it is known as Cognitive Radio. In such a scenario, multicarrier communication that transmits data across the channel in several frequency subcarriers at a lower data rate has gained prominence. Its appeal lies in the fact that it combats frequency selective fading. Two methods for implementing multicarrier modulation are non-contiguous orthogonal frequency division multiplexing (NCOFDM)and filter bank multicarrier modulation (FBMC). This thesis aims to implement a novel FBMC transmitter using software defined radio (SDR) with modulated filters based on a lowpass prototype. FBMCs employ two sets of bandpass filters called analysis and synthesis filters, one at the transmitter and the other at the receiver, in order to filter the collection of subcarriers being transmitted simultaneously in parallel frequencies. The novel aspect of this research is that a wireless transmitter based on non-contiguous FBMC is being used to design spectrally agile waveforms for dynamic spectrum access as opposed to the more popular NC-OFDM. Better spectral containment and bandwidth efficiency, combined with lack of cyclic prefix processing, makes it a viable alternative for NC-OFDM. The main aim of this thesis is to prove that FBMC can be practically implemented for wireless communications. The practicality of the method is tested by transmitting the FBMC signals real time by using the Simulink environment and USRP2 hardware modules

Two-Path All-pass Based Half-Band Infinite Impulse Response Decimation Filters and the Effects of Their Non-Linear Phase Response on ECG Signal Acquisition

This paper is based on the novel use of a very high fidelity decimation filter chain for Electrocardiogram (ECG) signal acquisition and data conversion. The multiplier-free and multi-stage structure of the proposed filters lower the power dissipation while minimizing the circuit area which are crucial design constraints to the wireless noninvasive wearable health monitoring products due to the scarce operational resources in their electronic implementation. The decimation ratio of the presented filter is 128, working in tandem with a 1-bit 3rd order Sigma Delta (ΣΔ) modulator which achieves 0.04 dB passband ripples and -74 dB stopband attenuation. The work reported here investigates the non-linear phase effects of the proposed decimation filters on the ECG signal by carrying out a comparative study after phase correction. It concludes that the enhanced phase linearity is not crucial for ECG acquisition and data conversion applications since the signal distortion of the acquired signal, due to phase non-linearity, is insignificant for both original and phase compensated filters. To the best of the authors’ knowledge, being free of signal distortion is essential as this might lead to misdiagnosis as stated in the state of the art. This article demonstrates that with their minimal power consumption and minimal signal distortion features, the proposed decimation filters can effectively be employed in biosignal data processing units

Enhanced Spectrum Sensing Techniques for Cognitive Radio Systems

Due to the rapid growth of new wireless communication services and applications, much attention has been directed to frequency spectrum resources. Considering the limited radio spectrum, supporting the demand for higher capacity and higher data rates is a challenging task that requires innovative technologies capable of providing new ways of exploiting the available radio spectrum. Cognitive radio (CR), which is among the core prominent technologies for the next generation of wireless communication systems, has received increasing attention and is considered a promising solution to the spectral crowding problem by introducing the notion of opportunistic spectrum usage. Spectrum sensing, which enables CRs to identify spectral holes, is a critical component in CR technology. Furthermore, improving the efficiency of the radio spectrum use through spectrum sensing and dynamic spectrum access (DSA) is one of the emerging trends. In this thesis, we focus on enhanced spectrum sensing techniques that provide performance gains with reduced computational complexity for realistic waveforms considering radio frequency (RF) impairments, such as noise uncertainty and power amplifier (PA) non-linearities. The first area of study is efficient energy detection (ED) methods for spectrum sensing under non-flat spectral characteristics, which deals with relatively simple methods for improving the detection performance. In realistic communication scenarios, the spectrum of the primary user (PU) is non-flat due to non-ideal frequency responses of the devices and frequency selective channel conditions. Weighting process with fast Fourier transform (FFT) and analysis filter bank (AFB) based multi-band sensing techniques are proposed for overcoming the challenge of non-flat characteristics. Furthermore, a sliding window based spectrum sensing approach is addressed to detect a re-appearing PU that is absent in one time and present in other time. Finally, the area under the receiver operating characteristics curve (AUC) is considered as a single-parameter performance metric and is derived for all the considered scenarios. The second area of study is reduced complexity energy and eigenvalue based spectrum sensing techniques utilizing frequency selectivity. More specifically, novel spectrum sensing techniques, which have relatively low computational complexity and are capable of providing accurate and robust performance in low signal-to-noise ratio (SNR) with noise uncertainty, as well as in the presence of frequency selectivity, are proposed. Closed-form expressions are derived for the corresponding probability of false alarm and probability of detection under frequency selectivity due the primary signal spectrum and/or the transmission channel. The offered results indicate that the proposed methods provide quite significant saving in complexity, e.g., 78% reduction in the studied example case, whereas their detection performance is improved both in the low SNR and under noise uncertainty. Finally, a new combined spectrum sensing and resource allocation approach for multicarrier radio systems is proposed. The main contribution of this study is the evaluation of the CR performance when using wideband spectrum sensing methods in combination with water-filling and power interference (PI) based resource allocation algorithms in realistic CR scenarios. Different waveforms, such as cyclic prefix based orthogonal frequency division multiplexing (CP-OFDM), enhanced orthogonal frequency division multiplexing (E-OFDM) and filter bank based multicarrier (FBMC), are considered with PA nonlinearity type RF impairments to see the effects of spectral leakage on the spectrum sensing and resource allocation performance. It is shown that AFB based spectrum sensing techniques and FBMC waveforms with excellent spectral containment properties have clearly better performance compared to the traditional FFT based spectrum sensing techniques with the CP-OFDM. Overall, the investigations in this thesis provide novel spectrum sensing techniques for overcoming the challenge of noise uncertainty with reduced computational complexity. The proposed methods are evaluated under realistic signal models

Channelization for Multi-Standard Software-Defined Radio Base Stations

As the number of radio standards increase and spectrum resources come under more pressure, it becomes ever less efficient to reserve bands of spectrum for exclusive use by a single radio standard. Therefore, this work focuses on channelization structures compatible with spectrum sharing among multiple wireless standards and dynamic spectrum allocation in particular. A channelizer extracts independent communication channels from a wideband signal, and is one of the most computationally expensive components in a communications receiver. This work specifically focuses on non-uniform channelizers suitable for multi-standard Software-Defined Radio (SDR) base stations in general and public mobile radio base stations in particular. A comprehensive evaluation of non-uniform channelizers (existing and developed during the course of this work) shows that parallel and recombined variants of the Generalised Discrete Fourier Transform Modulated Filter Bank (GDFT-FB) represent the best trade-off between computational load and flexibility for dynamic spectrum allocation. Nevertheless, for base station applications (with many channels) very high filter orders may be required, making the channelizers difficult to physically implement. To mitigate this problem, multi-stage filtering techniques are applied to the GDFT-FB. It is shown that these multi-stage designs can significantly reduce the filter orders and number of operations required by the GDFT-FB. An alternative approach, applying frequency response masking techniques to the GDFT-FB prototype filter design, leads to even bigger reductions in the number of coefficients, but computational load is only reduced for oversampled configurations and then not as much as for the multi-stage designs. Both techniques render the implementation of GDFT-FB based non-uniform channelizers more practical. Finally, channelization solutions for some real-world spectrum sharing use cases are developed before some final physical implementation issues are considered

Design and implementation of components for renewably-powered base-stations with heterogeneous access channel

Providing high-speed broadband services in remote areas can be a challenging task, especially because of the lack of network infrastructure. As typical broadband technologies are often expensive to deploy, they require large investment from the local authorities. Previous studies have shown that a viable alternative is to use wireless base stations with high-throughput point to point (PTP) backhaul links. With base stations comes the problem of powering their systems, it is tackled in this thesis by relying on renewable energy harvesting, such as solar panels or wind turbines. This thesis, in the context of the sustainable cellular network harvesting ambient energy (SCAVENGE) project, aims to contribute to a reliable and energy efficient solution to this problem, by adjusting the design of an existing multi-radio energy harvesting base station. In Western Europe, 49 channels of 8 MHz were used for analogue TV transmissions, ranging from 470 MHz (Channel 21) to 862 MHz (Channel 69); this spectrum, now partially unused due to the digital television (DTV) switch-over, has been opened to alternative uses by the regulatory authorities. Using this newly freed ultra high frequency (UHF) range, also known as TV white space (TVWS), can offer reliable low-cost broadband access to housings and businesses in low-density areas. While UHF transmitters allow long range links, the overcrowding of the TV spectrum limits the achievable throughput; to increase the capacity of such TVWS rural broadband base station the UHF radio has previously been combined with a lower-range higher throughput GHz radio like Wireless Fidelity (WiFi). From the regulatory constraints of TVWS applications arises the need for frequency agile transceivers that observe strict spectral mask requirements, this guided previous works towards discrete Fourier transform (DFT) modulated filter-bank multicarrier (FBMC) systems. These systems are numerically efficient, as they permit the up-and-down conversion of the 40 TV channels at the cost of a single channel transceiver and the modulating transform. Typical implementations rely on power-of two fast Fourier transforms (FFTs); however the smallest transform covering the full 40 channels of the TVWS spectrum is a 64 points wide, thus involving 24 unused channels. In order to attain a more numerically-efficient implemented design, we introduce the use of mixed-radix FFTs modulating transform. Testing various sizes and architectures, this approach provides up to 6.7% of energy saving compared to previous designs. Different from orthogonal frequency-division multiplexing (OFDM), FBMC systems are generally expected to be more robust to synchronisation errors, as oversampled FBMC systems can include a guard band, and even in a doubly-dispersive channel, inter-carrier interference (ICI) can be considered negligible. Even though sub-channels can be treated independently—i.e. without the use of cross-terms—they still require equalisation. We introduce a per-band equalisation, amongst different options, a robust and fast blind approach based on a concurrent constant modulus (CM)/decision directed (DD) fractionally-space equaliser (FSE) is selected. The selected approach is capable of equalising a frequency-selective channel. Furthermore the proposed architecture is advantageous in terms of power consumption and implementation cost. After focussing on the design of the radio for TVWS transmission, we address a multi-radio user assignment problem. Using various power consumption and harvesting models for the base station, we formulate two optimisation problems, the first focuses on the base station power consumption, while the second concentrates on load balancing. We employ a dynamic programming approach to optimise the user assignment. The use of such algorithms could allow a downsizing of the power supply systems (harvesters and batteries), thus reducing the cost of the base station. Furthermore the algorithms provide a better balance between the number of users assigned to each network, resulting in a higher quality of service (QoS) and energy efficiency.Providing high-speed broadband services in remote areas can be a challenging task, especially because of the lack of network infrastructure. As typical broadband technologies are often expensive to deploy, they require large investment from the local authorities. Previous studies have shown that a viable alternative is to use wireless base stations with high-throughput point to point (PTP) backhaul links. With base stations comes the problem of powering their systems, it is tackled in this thesis by relying on renewable energy harvesting, such as solar panels or wind turbines. This thesis, in the context of the sustainable cellular network harvesting ambient energy (SCAVENGE) project, aims to contribute to a reliable and energy efficient solution to this problem, by adjusting the design of an existing multi-radio energy harvesting base station. In Western Europe, 49 channels of 8 MHz were used for analogue TV transmissions, ranging from 470 MHz (Channel 21) to 862 MHz (Channel 69); this spectrum, now partially unused due to the digital television (DTV) switch-over, has been opened to alternative uses by the regulatory authorities. Using this newly freed ultra high frequency (UHF) range, also known as TV white space (TVWS), can offer reliable low-cost broadband access to housings and businesses in low-density areas. While UHF transmitters allow long range links, the overcrowding of the TV spectrum limits the achievable throughput; to increase the capacity of such TVWS rural broadband base station the UHF radio has previously been combined with a lower-range higher throughput GHz radio like Wireless Fidelity (WiFi). From the regulatory constraints of TVWS applications arises the need for frequency agile transceivers that observe strict spectral mask requirements, this guided previous works towards discrete Fourier transform (DFT) modulated filter-bank multicarrier (FBMC) systems. These systems are numerically efficient, as they permit the up-and-down conversion of the 40 TV channels at the cost of a single channel transceiver and the modulating transform. Typical implementations rely on power-of two fast Fourier transforms (FFTs); however the smallest transform covering the full 40 channels of the TVWS spectrum is a 64 points wide, thus involving 24 unused channels. In order to attain a more numerically-efficient implemented design, we introduce the use of mixed-radix FFTs modulating transform. Testing various sizes and architectures, this approach provides up to 6.7% of energy saving compared to previous designs. Different from orthogonal frequency-division multiplexing (OFDM), FBMC systems are generally expected to be more robust to synchronisation errors, as oversampled FBMC systems can include a guard band, and even in a doubly-dispersive channel, inter-carrier interference (ICI) can be considered negligible. Even though sub-channels can be treated independently—i.e. without the use of cross-terms—they still require equalisation. We introduce a per-band equalisation, amongst different options, a robust and fast blind approach based on a concurrent constant modulus (CM)/decision directed (DD) fractionally-space equaliser (FSE) is selected. The selected approach is capable of equalising a frequency-selective channel. Furthermore the proposed architecture is advantageous in terms of power consumption and implementation cost. After focussing on the design of the radio for TVWS transmission, we address a multi-radio user assignment problem. Using various power consumption and harvesting models for the base station, we formulate two optimisation problems, the first focuses on the base station power consumption, while the second concentrates on load balancing. We employ a dynamic programming approach to optimise the user assignment. The use of such algorithms could allow a downsizing of the power supply systems (harvesters and batteries), thus reducing the cost of the base station. Furthermore the algorithms provide a better balance between the number of users assigned to each network, resulting in a higher quality of service (QoS) and energy efficiency

Design of a reusable distributed arithmetic filter and its application to the affine projection algorithm

Digital signal processing (DSP) is widely used in many applications spanning the spectrum from audio processing to image and video processing to radar and sonar processing. At the core of digital signal processing applications is the digital filter which are implemented in two ways, using either finite impulse response (FIR) filters or infinite impulse response (IIR) filters. The primary difference between FIR and IIR is that for FIR filters, the output is dependent only on the inputs, while for IIR filters the output is dependent on the inputs and the previous outputs. FIR filters also do not sur from stability issues stemming from the feedback of the output to the input that aect IIR filters. In this thesis, an architecture for FIR filtering based on distributed arithmetic is presented. The proposed architecture has the ability to implement large FIR filters using minimal hardware and at the same time is able to complete the FIR filtering operation in minimal amount of time and delay when compared to typical FIR filter implementations. The proposed architecture is then used to implement the fast affine projection adaptive algorithm, an algorithm that is typically used with large filter sizes. The fast affine projection algorithm has a high computational burden that limits the throughput, which in turn restricts the number of applications. However, using the proposed FIR filtering architecture, the limitations on throughput are removed. The implementation of the fast affine projection adaptive algorithm using distributed arithmetic is unique to this thesis. The constructed adaptive filter shares all the benefits of the proposed FIR filter: low hardware requirements, high speed, and minimal delay.Ph.D.Committee Chair: Anderson, Dr. David V.; Committee Member: Hasler, Dr. Paul E.; Committee Member: Mooney, Dr. Vincent J.; Committee Member: Taylor, Dr. David G.; Committee Member: Vuduc, Dr. Richar

Channel estimation techniques for filter bank multicarrier based transceivers for next generation of wireless networks

A dissertation submitted to Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Engineering (Electrical and Information Engineering), August 2017The fourth generation (4G) of wireless communication system is designed based on the principles of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) where the cyclic prefix (CP) is used to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) in order to achieve higher data rates in comparison to the previous generations of wireless networks. Various filter bank multicarrier systems have been considered as potential waveforms for the fast emerging next generation (xG) of wireless networks (especially the fifth generation (5G) networks). Some examples of the considered waveforms are orthogonal frequency division multiplexing with offset quadrature amplitude modulation based filter bank, universal filtered multicarrier (UFMC), bi-orthogonal frequency division multiplexing (BFDM) and generalized frequency division multiplexing (GFDM). In perfect reconstruction (PR) or near perfect reconstruction (NPR) filter bank designs, these aforementioned FBMC waveforms adopt the use of well-designed prototype filters (which are used for designing the synthesis and analysis filter banks) so as to either replace or minimize the CP usage of the 4G networks in order to provide higher spectral efficiencies for the overall increment in data rates. The accurate designing of the FIR low-pass prototype filter in NPR filter banks results in minimal signal distortions thus, making the analysis filter bank a time-reversed version of the corresponding synthesis filter bank. However, in non-perfect reconstruction (Non-PR) the analysis filter bank is not directly a time-reversed version of the corresponding synthesis filter bank as the prototype filter impulse response for this system is formulated (in this dissertation) by the introduction of randomly generated errors. Hence, aliasing and amplitude distortions are more prominent for Non-PR. Channel estimation (CE) is used to predict the behaviour of the frequency selective channel and is usually adopted to ensure excellent reconstruction of the transmitted symbols. These techniques can be broadly classified as pilot based, semi-blind and blind channel estimation schemes. In this dissertation, two linear pilot based CE techniques namely the least square (LS) and linear minimum mean square error (LMMSE), and three adaptive channel estimation schemes namely least mean square (LMS), normalized least mean square (NLMS) and recursive least square (RLS) are presented, analyzed and documented. These are implemented while exploiting the near orthogonality properties of offset quadrature amplitude modulation (OQAM) to mitigate the effects of interference for two filter bank waveforms (i.e. OFDM/OQAM and GFDM/OQAM) for the next generation of wireless networks assuming conditions of both NPR and Non-PR in slow and fast frequency selective Rayleigh fading channel. Results obtained from the computer simulations carried out showed that the channel estimation schemes performed better in an NPR filter bank system as compared with Non-PR filter banks. The low performance of Non-PR system is due to the amplitude distortion and aliasing introduced from the random errors generated in the system that is used to design its prototype filters. It can be concluded that RLS, NLMS, LMS, LMMSE and LS channel estimation schemes offered the best normalized mean square error (NMSE) and bit error rate (BER) performances (in decreasing order) for both waveforms assuming both NPR and Non-PR filter banks. Keywords: Channel estimation, Filter bank, OFDM/OQAM, GFDM/OQAM, NPR, Non-PR, 5G, Frequency selective channel.CK201

Rethinking Wireless: Building Next-Generation Networks

We face a growing challenge to the design, deployment and management of wireless networks that largely stems from the need to operate in an increasingly spectrum-sparse environment, the need for greater concurrency among devices and the need for greater coordination between heterogeneous wireless protocols. Unfortunately, our current wireless networks lack interoperability, are deployed with fixed functions, and omit easy programmability and extensibility from their key design requirements. In this dissertation, we study the design of next-generation wireless networks and analyze the individual components required to build such an infrastructure. Re-designing a wireless architecture must be undertaken carefully to balance new and coordinated multipoint (CoMP) techniques with the backward compatibility necessary to support the large number of existing devices. These next-generation wireless networks will be predominantly software-defined and will have three components: (a) a wireless component that consists of software-defined radio resource units (RRUs) or access points (APs); (b) a software-defined backhaul control plane that manages the transfer of RF data between the RRUs and the centralized processing resource; and (c) a centralized datacenter/cloud compute resource that processes RF signal data from all attached RRUs. The dissertation addresses the following four key problems in next-generation networks: (1) Making Existing Wireless Devices Spectrum-Agile, (2) Cooperative Compression of the Wireless Backhaul, (3) Spectrum Coordination and (4) Spectrum Coordination.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102341/1/zontar_1.pd

NOVEL OFDM SYSTEM BASED ON DUAL-TREE COMPLEX WAVELET TRANSFORM

The demand for higher and higher capacity in wireless networks, such as cellular, mobile and local area network etc, is driving the development of new signaling techniques with improved spectral and power efficiencies. At all stages of a transceiver, from the bandwidth efficiency of the modulation schemes through highly nonlinear power amplifier of the transmitters to the channel sharing between different users, the problems relating to power usage and spectrum are aplenty. In the coming future, orthogonal frequency division multiplexing (OFDM) technology promises to be a ready solution to achieving the high data capacity and better spectral efficiency in wireless communication systems by virtue of its well-known and desirable characteristics. Towards these ends, this dissertation investigates a novel OFDM system based on dual-tree complex wavelet transform (D