Power allocation and linear precoding for wireless communications with finite-alphabet inputs

This dissertation proposes a new approach to maximizing data rate/throughput of practical communication system/networks through linear precoding and power allocation. First, the mutual information or capacity region is derived for finite-alphabet inputs such as phase-shift keying (PSK), pulse-amplitude modulation (PAM), and quadrature amplitude modulation (QAM) signals. This approach, without the commonly used Gaussian input assumptions, complicates the mutual information analysis and precoder design but improves performance when the designed precoders are applied to practical systems and networks. Second, several numerical optimization methods are developed for multiple-input multiple-output (MIMO) multiple access channels, dual-hop relay networks, and point-to-point MIMO systems. In MIMO multiple access channels, an iterative weighted sum rate maximization algorithm is proposed which utilizes an alternating optimization strategy and gradient descent update. In dual-hop relay networks, the structure of the optimal precoder is exploited to develop a two-step iterative algorithm based on convex optimization and optimization on the Stiefel manifold. The proposed algorithm is insensitive to initial point selection and able to achieve a near global optimal precoder solution. The gradient descent method is also used to obtain the optimal power allocation scheme which maximizes the mutual information between the source node and destination node in dual-hop relay networks. For point-to-point MIMO systems, a low complexity precoding design method is proposed, which maximizes the lower bound of the mutual information with discretized power allocation vector in a non-iterative fashion, thus reducing complexity. Finally, performances of the proposed power allocation and linear precoding schemes are evaluated in terms of both mutual information and bit error rate (BER). Numerical results show that at the same target mutual information or sum rate, the proposed approaches achieve 3-10dB gains compared to the existing methods in the medium signal-to-noise ratio region. Such significant gains are also indicated in the coded BER systems --Abstract, page iv-v

An Equilibrium Bid Markup Strategy

Setting a bid markup strategy is a very difficult task. Nevertheless, it is important to construction firms or consulting engineering companies because the development of successful bidding strategies is a key factor to their survival in business. Based on the two bidding criteria of the conditional profit ratio and the work force continuity, this short paper first presents the explicit expression of an equilibrium bid markup strategy in procurement auctions. However, the two bidding criteria conflict with each other and tradeoffs must be made. To make tradeoffs between the two bidding criteria, a new bid markup selection making model is then developed by Cobb-Douglas utility function. The model generalizes the classical expected profit model in the sense that the latter's objective function is only a special case of the former. The result shows that the relative importance of a bidding criterion to another has significant effect on the selection of the equilibrium bid markup strategyThis work was supported partly by the National Natural Science Foundation of China (No. 71001097 and 71171052) and China Postdoctoral Science Foundation (No. 201104167)S

Иностранные воинские захоронения Великой Отечественной войны в Челябинской области: результаты поисковых работ и современное состояние

<p>Index building time on varying <i>θ</i>.</p

Linear Precoding for Relay Networks with Finite-Alphabet Constraints

In this paper, we investigate the optimal precoding scheme for relay networks with finite-alphabet constraints. We show that the previous work utilizing various design criteria to maximize either the diversity order or the transmission rate with the Gaussian-input assumption may lead to significant loss for a practical system with finite constellation set constraint. A linear precoding scheme is proposed to maximize the mutual information for relay networks. We exploit the structure of the optimal precoding matrix and develop a unified two-step iterative algorithm utilizing the theory of convex optimization and optimization on the complex Stiefel manifold. Numerical examples show that this novel iterative algorithm achieves significant gains compared to its conventional counterpart.Comment: Accepted by IEEE Int. Conf. Commun. (ICC), Kyoto, Japan, 201

Quantification and scenario analysis of CO2 emissions from the central heating supply system in China from 2006 to 2025

Policies associated with the central heating supply system affect the livelihoods of people in China. With the extensive consumption of energy for central heating, large quantities of CO2 emissions are produced each year. Coal-fired heating boiler plants are the primary source of emissions; however, thermal power plants are becoming much more prevalent, and gas-fired heating boiler plants remain uncommon. This study quantified the amount of CO2 emitted from the central heating supply system in China using a mass balance method with updated emission factors from the IPCC. Emissions increased from 189.04 Tg to 319.39 Tg between 2006 and 2015. From a spatial perspective, regions with larger central heating areas, durations and coverages produced more CO2 emissions. The central heating method depends on the level of electric power consumption, policies and regulations, and resource reserves at the local scale. Compared with the use of only coal-fired heating boiler plants to provide central heating, using thermal power plants and gas-fired heating boiler plants reduced CO2 emissions by 98.19 Tg in 2015 in China. A comparison of the CO2 emissions under various central heating scenarios showed that emissions will be 520.97 Tg, 308.79 Tg and 191.86 Tg for business as usual, positive and optimal scenarios through 2025, respectively. China has acknowledged the considerable potential for reducing central heating and will make efforts to pursue improved heating strategies in the future

A General Theory of Correct, Incorrect, and Extrinsic Equivariance

Although equivariant machine learning has proven effective at many tasks, success depends heavily on the assumption that the ground truth function is symmetric over the entire domain matching the symmetry in an equivariant neural network. A missing piece in the equivariant learning literature is the analysis of equivariant networks when symmetry exists only partially in the domain. In this work, we present a general theory for such a situation. We propose pointwise definitions of correct, incorrect, and extrinsic equivariance, which allow us to quantify continuously the degree of each type of equivariance a function displays. We then study the impact of various degrees of incorrect or extrinsic symmetry on model error. We prove error lower bounds for invariant or equivariant networks in classification or regression settings with partially incorrect symmetry. We also analyze the potentially harmful effects of extrinsic equivariance. Experiments validate these results in three different environments.Comment: Published at NeurIPS 202

Climate Resilience, Megalopolis Vulnerability and Spatial Distribution

This chapter takes three megalopolises including Guangdong-Hong Kong-Macao, Yangtze River Delta and Beijing-Tianjin-Hebei as research objects, firstly analyzes the connection relationship and megalopolis vulnerability among core cities in the context of regional integration. Secondly, we calculate there megalopolises to obtain the vulnerability of each city in 2018 Sex index. The results show that the central cities and economically underdeveloped cities of the three megalopolises are relatively vulnerable areas in the urban agglomerations, and areas have low sensitivity and high response. Finally, policy suggestions for megalopolis are given to improve the adaptive capacity of tackling climate change. The innovation of this chapter is to use spatial data to comprehensively evaluate and analyze the vulnerability, and to realize visualization in the map, which better reflects the distribution law and proposes a response to megalopolis vulnerability