192 research outputs found

    Resource allocation optimization for future wireless communication systems

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    To meet the ever-increasing requirements of high data rate, extremely low latency, and ubiquitous connectivity for the fifth generation (5G) and beyond 5G (B5G) wireless communications, there is imperious demands for advanced communication system design. Particularly, efficient resource allocation is regarded as the fundamental challenge whereas an effective way to improve system performance. The term ”resource” refers to scare quantities such as limited bandwidth, power and time in wireless communications. Moreover, the development of wireless communication systems is accompanied by the innovation of applied technologies. Motivated by the above observations, efficient resource allocation strategies for several promising 5G and B5G technologies in terms of non-orthogonal multiple access (NOMA), mobile edge computing (MEC) and Long Range (LoRa) are addressed and investigated in this thesis. Firstly, the strong user’s data rate maximization problem for simultaneous wireless information and power transfer (SWIPT)-enabled cooperative NOMA system, considering the presence of channnel uncertainties, is proposed and investigated. Two major channel uncertainty design criteria in terms of the outage-based constraint design and the worst-case based optimization are adopted. In addition to the high-complexity optimal two-dimensional exhaustive search method, the low-complexity suboptimal solution is further proposed. The advantages of SWIPT-enabled cooperation in robust NOMA are confirmed with simulations. Secondly, considering the application of NOMA and user cooperation (UC) in a wireless powered MEC under the non-linear energy harvesting model, a computation efficiency maximization problem subject to the quality of service (QoS) and power budget constraint, is studied and analyzed. The formulated problem is nonconvex, which is challenging to solve. The semidefinite relaxation (SDR) approach is first applied, then the sequential convex approximation (SCA)-based solution is further proposed to maximize the system computation efficiency. Finally, taking into consideration the aspect of energy efficiency (EE), this thesis investigates the energy efficient resource allocation in LoRa networks to maximize the system EE (SEE) and the minimal EE (MEE) of LoRa users, respectively. The energy efficient resource allocation is formulated as NP-hard problems. A low-complexity user scheduling scheme based on matching theory is proposed to allocate users to channels, then the heuristic SF assignment solution is designed for LoRa users scheduled on the same channel. The optimal power allocation strategy is further proposed to maximize the corresponding EE

    Robust Transmit Designs for Secrecy Rate Constrained MISO NOMA System

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    This paper studies the secure transmission for downlink multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) system in which imperfect channel state information (CSI) of the eavesdropper links is considered. We propose the novel robust beamforming strategies for the direct transmission NOMA (DT NOMA) and cooperative jamming NOMA (CJ NOMA) with a helper. We formulate our problem as the worst-case sum power minimization subject to secrecy rate constraint. The semidefinite relaxation (SDR) method is firstly applied to relax the quadratic terms and rank-one optimality is proved. Then an iterative algorithm based on successive convex approximation (SCA) is proposed to transform the nonconvex problem into convex approximations. Simulation results show that both the proposed NOMA schemes outperform the orthogonal multiple scheme, and CJ NOMA scheme can achieve much better system performance gain than DT NOMA scheme

    Robust Transmit Beamforming for SWIPT-Enabled Cooperative NOMA with Channel Uncertainties

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    In this paper, we study the robust beamforming design for a simultaneous wireless information and power transfer (SWIPT) enabled system, with cooperative nonorthogonal multiple access (NOMA) protocol applied. A novel cooperative NOMA scheme is proposed, where the strong user with better channel conditions adopts power splitting (PS) scheme and acts as an energy-harvesting relay to transmit information to the weak user. The presence of channel uncertainties is considered and incorporated in our formulations to improve the design robustness and communication reliability. Specifically, only imperfect channel state information (CSI) is assumed to be available at the base station (BS), due to the reason that the BS is far away from both users and suffers serious feedback delay. To comprehensively address the channel uncertainties, two major design criteria are adopted, which are the outage-based constraint design and the worst-case based optimization. Then, our aim is to maximize the strong user’s data rate, by optimally designing the robust transmit beamforming and PS ratio, while guaranteeing the correct decoding of the weak user. With two different channel uncertainty models respectively incorporated, the proposed formulations yield to challenging nonconvex optimization problems. For the outage-based constrained optimization, we first conservatively approximate the probabilistic constraints with the Bernstein-type inequalities, which are then globally solved by two-dimensional exhaustive search. To further reduce the complexity, an efficient low-complexity algorithm is then proposed with the aid of successive convex approximation (SCA). For the worst-case based scenario, we firstly apply semidefinite relaxation (SDR) method to relax the quadratic terms and prove the rank-one optimality. Then the nonconvex max-min optimization problem is readily transformed into convex approximations based on S-procedure and SCA. Simulation results show that for both channel uncertainty models, the proposed algorithms can converge within a few iterations, and the proposed SWIPT-enabled robust cooperative NOMA system achieves better system performance than existing protocols

    Analysis of Lake Stratification and Mixing and Its Influencing Factors over High Elevation Large and Small Lakes on the Tibetan Plateau

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    Lake stratification and mixing processes can influence gas and energy transport in the water column and water–atmosphere interactions, thus impacting limnology and local climate. Featuring the largest high-elevation inland lake zone in the world, comprehensive and comparative studies on the evolution of lake stratification and mixing and their driving forces are still quite limited. Here, using valuable temperature chain measurements in four large lakes (Nam Co, Dagze Co, Bangong Co, and Paiku Co) and a “small lake” adjacent to Nam Co, our objectives are to investigate the seasonal and diurnal variations of epilimnion depth (Ep, the most important layer in stratification and mixing process) and to analyze the driving force differences between “small lake” and Nam Co. Results indicate that Ep estimated by the methods of the absolute density difference (&lt;0.1 kg m−3) from the surface and the Lake-Analyzer were quite similar, with the former being more reliable and widely applicable. The stratification and mixing in the four large lakes showed a dimictic pattern, with obvious spring and autumn turnovers. Additionally, the stratification form during heat storage periods, with Ep quickly locating at depths of approximately 10–15 m, and, after that, increasing gradually to the lake bottom. Additionally, the diurnal variation in Ep can be evidenced both in the large and small lakes when temperature measurements above 3 m depth are included. For Nam Co, the dominant influencing factors for the seasonal variation of Ep were the heat budget components (turbulent heat fluxes and radiation components), while wind speed only had a relatively weak positive correlation (r = 0.23). In the “small lake”, radiation components and wind speed show high negative (r = −0.43 to −0.59) and positive (r = 0.46) correlation, with rare correlations for turbulent heat flux. These reported characteristics have significance for lake process modeling and evaluation in these high-elevation lakes.</p

    Long-term variations in actual evapotranspiration over the Tibetan Plateau

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    Actual terrestrial evapotranspiration (ETa_{a}) is a key parameter controlling land–atmosphere interaction processes and water cycle. However, spatial distribution and temporal changes in ETa_{a} over the Tibetan Plateau (TP) remain very uncertain. Here we estimate the multiyear (2001–2018) monthly ETa_{a} and its spatial distribution on the TP by a combination of meteorological data and satellite products. Validation against data from six eddy-covariance monitoring sites yielded root-mean-square errors ranging from 9.3 to 14.5 mm per month and correlation coefficients exceeding 0.9. The domain mean of annual ETa_{a} on the TP decreased slightly (−1.45 mm yr1^{-1}, p90° E) but decreased significantly at a rate of −5.52 mm yr1^{-1} (p<0.05) in the western sector of the TP (long <90° E). In addition, the decreases in annual ETa_{a} were pronounced in the spring and summer seasons, while almost no trends were detected in the autumn and winter seasons. The mean annual ETa_{a} during 2001–2018 and over the whole TP was 496±23 mm. Thus, the total evapotranspiration from the terrestrial surface of the TP was 1238.3±57.6 km3 yr1^{-1}. The estimated ETa_{a} product presented in this study is useful for an improved understanding of changes in energy and water cycle on the TP. The dataset is freely available at the Science Data Bank (https://doi.org/10.11922/sciencedb.t00000.00010; Han et al., 2020b) and at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Hydro.tpdc.270995, Han et al., 2020a)

    Outage Constrained Robust Beamforming Design for SWIPT-Enabled Cooperative NOMA System

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    We investigate the robust beamforming design for a simultaneous wireless information and power transfer (SWIPT) enabled system, with the cooperative non-orthogonal multiple access (NOMA) protocol applied. A novel cooperative NOMA scheme is proposed, where a strong user with better channel conditions adopts power splitting (PS) scheme and acts as an energy-harvesting relay to forward the decoded signal to the weak user. The presence of channel uncertainties is considered by introducing the outage-based constraints of signal to interference plus noise ratio (SINR). Specifically, it is assumed that only imperfect channel state information (CSI) is known at the base station (BS), due to the reason that the BS is far away from both users and suffers serious feedback delay. Our aim is to maximize the strong user's data rate, by optimally designing the robust transmit beamforming and PS ratio, while guaranteeing the correct decoding of the weak user. The proposed formulation yields to a challenging nonconvex optimization problem. To solve it, we first approximate the probabilistic constraints with the Bernstein-type inequalities, which can then be globally solved by two-dimensional exhaustive search. To further reduce the complexity, an efficient low-complexity algorithm is proposed with the aid of successive convex approximation (SCA). Numerical results show that the proposed algorithm converges quickly, and the proposed SWIPT-enabled robust cooperative NOMA system achieves better performance than existing protocols

    Plasma noise in TianQin time delay interferometry

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    TianQin is a proposed geocentric space-based gravitational wave observatory mission, which requires time-delay interferometry (TDI) to cancel laser frequency noise. With high demands for precision, solar-wind plasma environment at 105\sim 10^5 km above the Earth may constitute a non-negligible noise source to laser interferometric measurements between satellites, as charged particles perturb the refractivity along light paths. In this paper, we first assess the plasma noises along single links from space-weather models and numerical orbits, and analyze the time and frequency domain characteristics. Particularly, to capture the plasma noise in the entire measurement band of 104110^{-4} - 1 Hz, we have performed additional space-weather magnetohydrodynamic simulations in finer spatial and temporal resolutions and utilized Kolmogorov spectra in high-frequency data generation. Then we evaluate the residual plasma noises of the first- and second-generation TDI combinations. Both analytical and numerical estimations have shown that under normal solar conditions the plasma noise after TDI is less than the secondary noise requirement. Moreover, TDI is shown to exhibit moderate suppression on the plasma noise below 102\sim 10^{-2} Hz due to noise correlation between different arms, when compared with the secondary noise before and after TDI.Comment: 12 pages, 15 figures, accepted by Phys. Rev.

    WR-ONE2SET: Towards Well-Calibrated Keyphrase Generation

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    Keyphrase generation aims to automatically generate short phrases summarizing an input document. The recently emerged ONE2SET paradigm (Ye et al., 2021) generates keyphrases as a set and has achieved competitive performance. Nevertheless, we observe serious calibration errors outputted by ONE2SET, especially in the over-estimation of \varnothing token (means "no corresponding keyphrase"). In this paper, we deeply analyze this limitation and identify two main reasons behind: 1) the parallel generation has to introduce excessive \varnothing as padding tokens into training instances; and 2) the training mechanism assigning target to each slot is unstable and further aggravates the \varnothing token over-estimation. To make the model well-calibrated, we propose WR-ONE2SET which extends ONE2SET with an adaptive instance-level cost Weighting strategy and a target Re-assignment mechanism. The former dynamically penalizes the over-estimated slots for different instances thus smoothing the uneven training distribution. The latter refines the original inappropriate assignment and reduces the supervisory signals of over-estimated slots. Experimental results on commonly-used datasets demonstrate the effectiveness and generality of our proposed paradigm.Comment: EMNLP202
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