9 research outputs found

    Census Tract License Areas: Disincentive for Sharing the 3.5GHz band?

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    Flexible licensing model is a necessary enabler of the technical and procedural complexities of Spectrum Access System (SAS)-based sharing framework. The purpose of this study is to explore the effectiveness of 3.5GHz Licensing Framework - based on census tracts as area units, areas whose main characteristic is population. As such, the boundary of census tract does not follow the edge of wireless network coverage. We demonstrate why census tracts are not suitable for small cell networks licensing, by (1) gathering and analysing the official census data, (2) exploring the boundaries of census tracts which are in the shape of nonconvex polygons and (3) giving a measure of effectiveness of the licensing scheme through metrics of area loss and the number of people per census tract with access to spectrum. Results show that census tracts severely impact the effectiveness of the licensing framework since almost entire strategically important cities in the U.S. will not avail from spectrum use in 3.5GHz band. Our paper does not seek to challenge the core notion of geographic licensing concept, but seeks a corrective that addresses the way the license is issued for a certain area of operation. The effects that inappropriate size of the license has on spectrum assignments lead to spectrum being simply wasted in geography, time and frequency or not being assigned in a fair manner. The corrective is necessary since the main goal of promoting innovative sharing in 3.5 GHz band is to put spectrum to more efficient use.Comment: 7 pages, 5 figures, conferenc

    PSUN: An OFDM-Pulsed Radar Coexistence Technique with Application to 3.5 GHz LTE

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    OFDM Waveform Optimisation for Joint Communications and Sensing

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    Radar systems are radios to sense objects in their surrounding environment. These operate at a defined set of frequency ranges. Communication systems are used to transfer information between two points. In the present day, proliferation of mobile devices and the advancement of technology have led to communication systems being ubiquitous. This has made these systems to operate at the frequency bands already used by the radar systems. Thus, the communication signal interferes a radar receiver and vice versa, degrading performance of both systems. Different methods have been proposed to combat this phenomenon. One of the novel topics in this is the RF convergence, where a given bandwidth is used jointly by both systems. A differentiation criterion must be adopted between the two systems so that a receiver is able to separately extract radar and communication signals. The hardware convergence due to the emergence of software-defined radios also motivated a single system be used for both radar and communication. A joint waveform is adopted for both radar and communication systems, as the transmit signal. As orthogonal frequency-division multiplexing (OFDM) waveform is the most prominent in mobile communications, it is selected as the joint waveform. Considering practical cellular communication systems adopting OFDM, there often exist unused subcarriers within OFDM symbols. These can be filled up with arbitrary data to improve the performance of the radar system. This is the approach used, where the filling up is performed through an optimisation algorithm. The filled subcarriers are termed as radar subcarriers while the rest as communication subcarriers, throughout the thesis. The optimisation problem minimises the Cramer--Rao lower bounds of the delay and Doppler estimates made by the radar system subject to a set of constraints. It also outputs the indices of the radar and communication subcarriers within an OFDM symbol, which minimise the lower bounds. The first constraint allocates power between radar and communication subcarriers depending on their subcarrier ratio in an OFDM symbol. The second constraint ensures the peak-to-average power ratio (PAPR) of the joint waveform has an acceptable level of PAPR. The results show that the optimised waveform provides significant improvement in the Cramer--Rao lower bounds compared with the unoptimised waveform. In compensation for this, the power allocated to the communication subcarriers needs to be reduced. Thus, improving the performances of the radar and communication systems are a trade-off. It is also observed that for the minimum lower bounds, radar subcarriers need to be placed at the two edges of an OFDM symbol. Optimisation is also seen to improve the estimation performance of a maximum likelihood estimator, concluding that optimising the subcarriers to minimise a theoretical bound enables to achieve improvement for practical systems

    PAPR Reduction Solutions for 5G and Beyond

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    The latest fifth generation (5G) wireless technology provides improved communication quality compared to earlier generations. The 5G New Radio (NR), specified by the 3rd Generation Partnership Project (3GPP), addresses the modern requirements of the wireless networks and targets improved communication quality in terms of for example peak data rates, latency and reliability. On the other hand, there are still various crucial issues that impact the implementation and energy-efficiency of 5G NR networks and their different deployments. The power-efficiency of transmitter power amplifiers (PAs) is one of these issues. The PA is an important unit of a communication system, which is responsible from amplifying the transmit signal towards the antenna. Reaching high PA power-efficiency is known to be difficult when the transmit waveform has a high peak-to-average power ratio (PAPR). The cyclic prefix (CP)-orthogonal frequencydivision multiplexing (OFDM) that is the main physical-layer waveform of 5G NR, suffers from such high PAPR challenge. There are generally many PAPR reduction methods proposed in the literature, however, many of these have either very notable computational complexity or impose substantial inband distortion. Moreover, 5G NR has new features that require redesigning the PAPR reduction methods. In line with these, the first contribution of this thesis is the novel frequencyselective PAPR reduction concept, where clipping noise is shaped in a frequencyselective manner over the active passband. This concept is in line with the 5G NR, where aggressive frequency-domain multiplexing is considered as an important feature. Utilizing the frequency-selective PAPR reduction enables the realization of the heterogeneous resource utilization within one passband. The second contribution of this thesis is the frequency-selective single-numerology (SN) and mixed-numerology (MN) PAPR reduction methods. The 5G NR targets utilizing different physical resource blocks (PRBs) and bandwidth parts (BWPs) within one passband flexibly. Yet, existing PAPR reduction methods do not exploit these features. Based on this, novel algorithms utilizing PRB and BWP level control of clipping noise are designed to meet error vector magnitude (EVM) limits of the modulations while reducing the PAPR. TheMNallocation has one critical challenge as inter numerology interference (INI) emerges after aggregation of subband signals. Proposed MN PAPR reduction algorithm overcomes this issue by cancelling INI within the PAPR reduction loop, which has not been considered earlier. The third contribution of this thesis is the proposal of two novel non-iterative PAPR reduction methods. First method utilizes the fast-convolution filteredOFDM (FC-F-OFDM) that has excellent spectral containment, and combines it with clipping. Moreover, clipping noise is also allocated to guard bands by filter passband extension (FPE) and clipping noise in out-of-band (OOB) regions is essentially filtered through FC filtering. The second method is the guard-tone reservation (GTR) which is applied to discrete Fourier transform-spread-OFDM (DFT-s-OFDM). Uniquely, GTR estimates the time domain peaks in data symbol domain before inverse fast Fourier transform (IFFT), and uses guard band tones for PAPR reduction. The fourth contribution of the thesis is the design of two novel machine learning (ML) algorithms that improve the drawbacks of frequency-selective PAPRreduction. The first ML algorithm, PAPRer, models the nonlinear relation between the PAPR target and the realized PAPR value. Then, it auto-tunes the optimal PAPR target and this way minimizes the realized PAPR. The second ML algorithm, one-shot clipping-and-filtering (OSCF), solves the complexity problem of iterative clipping and filtering (ICF)-like methods by generating proper approximated clipping noise signal after running only one iteration, leading to very efficient PAPR reduction. Finally, an over-arching contribution of this thesis is the experimental validation of the performance benefits of the proposed methods by considering realistic 5GNR uplink (UL) and downlink (DL) testbeds that include realistic PAs and associated hardware. It is very important to confirm the practical benefits of the proposed methods and, this is realized with the conducted experimental work
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