Among most of the message scheduling strategies for low-density parity-check (LDPC) codes, the dynamic scheduling strategy behaves best in error correction performance. Dynamic selection is an ...integral part of dynamic scheduling decoding, which plays a decisive role throughout the decoding process. Usually, the dynamic selection strategy based on the message residuals only is employed in dynamic decoding algorithms, while other potentials of the dynamic selection strategy are rarely cared about. In this paper, we propose the triple judgment dynamic selection strategy combined with a Stability Criterion. Interestingly, the new strategy can be well applied to two different dynamic algorithms, namely, the V-VCRBP and the V-CVRBP algorithms. The proposed strategy has a great advantage: locating the message to be preferentially updated is extremely quick and accurate. Simulation results demonstrate that the V-VCRBP algorithm outperforms existing decoding algorithms in terms of BER performance and convergence speed, while the V-CVRBP algorithm has good error correction performance with a lower computational complexity.
In this paper, we study linear transceiver designs for indoor visible light communications (VLCs) with multiple light emitting diodes (LEDs). Specifically, we investigate VLCs including white ...emitting diodes and VLCs including red/green/blue (RGB) LEDs. The transmitter precoding and the offset are jointly designed by considering certain key practical lighting constraints, such as optical power, non-negativeness, and color illumination. Various non-convex transceiver design problems are formulated aiming to minimize total mean-square-error to improve transmission reliability. We show that for multi-input single-output white VLCs, the optimal precoding reduces to a simple LED selection strategy. For multi-input multi-output (MIMO) white VLCs, we prove that the optimization problem with multiple constraints can be equivalently simplified to a problem with single constraint, which enables us to propose efficient algorithms to search local optimal solutions. For MIMO RGB VLCs, by using certain useful transformations, we show that the precoding design is equivalent to covariance matrix design of transmit signals, which can be further transformed to a convex optimization problem. To develop an algorithm to find the optimal solution, we derive the optimal structure of the covariance matrix and show that the optimal solution can be obtained via a water-filling approach. Extensive simulation results are provided to verify the performance of the proposed designs.
An uplink multi-user tracking problem aided by multiple passive reconfigurable intelligent surfaces (RISs) is addressed in this work. Under a near-field circumstance, a multi-antenna base station ...(BS) localizes multiple moving single-antenna users by processing the received signals transmitted by users and reflected by RISs. Considering the users’ mobility and the potential obstruction of line-of-sight paths, a multi-user tracking system based on the extended Kalman filter (EKF) which fully exploits the temporal correlations between each user’s coordinate changes is designed. Then, the Bayesian Cramér–Rao bound (BCRB) of tracking errors is derived in a pattern consistent with the EKF process. Subsequently, an optimization scheme for passive phase shift design at the RISs is devised by minimizing the derived BCRB and is solved using the Gradient Descent method. Numerical results indicate that the accuracy of our tracking algorithm can approach the BCRB. With abundant RISs deployed and optimized, high-precision multi-user tracking via a single BS can be realized even in harsh localization environments.
Physical transceiver impairments can degrade the performance of wireless communication systems significantly. Although partial impairments can be mitigated by some compensation algorithms, residual ...impairments still have substantial effects. In this letter, we investigate the joint source/relay precoding design for the multiple-input multiple-output two-way amplify and forward relay systems by considering hardware impairments. Unlike the ideal case, considering the effect of hardware impairments makes the precoding design more challenging. To tackle the problem, we use certain rules of trace operator to convert the original design problem and develop an iterative algorithm to find a local optimal solution. Simulation results show that the system is more sensitive to hardware impairments in the high signal noise ratio regimes and neglect of the residual hardware impairments will deteriorate the system performance significantly.
Magnetic induction (MI) has been proven to be an efficient wireless communication technique for overcoming the transmission challenges in some very harsh propagation environments, such as ...underground, underwater, etc. For a random distributed MI ad hoc network in a 3-D space composed of uniform medium, we propose a method for determining the required node density and transmitting power that creates an almost surely fully connected network. For which we involve an MI path-loss model and consider the effect of eddy currents, the effective coverage space and the expected node degree of an MI node are then calculated by a Lambert W-function-based integration. Finally, we propose optimized frequency selection methods for improving the connectivity of MI networks. In addition to an ideal frequency-switching optimization method, we provide for engineering applications a practical frequency-fixed optimization method, which is based on the gradient descent algorithm, where an improved initialization is used to reduce iterations.
Blockchain for finance: A survey Wu, Hanjie; Yao, Qian; Liu, Zhenguang ...
IET blockchain,
June 2024, Letnik:
4, Številka:
2
Journal Article
Recenzirano
Odprti dostop
As an innovative technology for enhancing authenticity, security, and risk management, blockchain is being widely adopted in trade and finance systems. The unique capabilities of blockchain, such as ...immutability and transparency, enable new business models of distributed data storage, point‐to‐point transactions, and decentralized autonomous organizations. Here, the authors focus on blockchain‐based securities trading, in which blockchain technology plays a vital role in financial services as it ultimately lifts trust and frees the need for third‐party verification by using consensus‐based verification. The 12 most popular blockchain platforms are investigated and 6 platforms that are related to finance are elaborated on, seeking to provide a panorama of securities trading practices. Meanwhile, this survey provides a comprehensive summary of blockchain‐based securities trading applications. Numerous practical applications of blockchain‐based securities trading are gathered and they are categorized into four distinct categories. For each category, a typical example is introduced and how blockchain contributes to solving the key problems faced by FinTech companies and researchers explained. Finally, interesting observations are provided ranging from mainstream blockchain‐based financial institutions to security issues of decentralized finance applications, aiming to picture the current blockchain ecosystem in finance.
This paper pictures the current blockchain ecosystem in finance. It summarizes the challenges of the current blockchain applications in the global financial sector and provides an implementation proposal about a new blockchain‐based financial infrastructure tailored for the Chinese financial market.
In this letter, we propose a link-addition strategy, called reduction structural hole (RSH), to enhance the network transport efficiency for scale-free networks. Instead of using global parameters of ...betweenness centrality and shortest path length that are commonly used in link-addition approaches, we turn to the theory of structural hole to design the new link-addition strategy. RSH applies the theory from social science to guide how to add links to the existing topology and uses network constraint index that requires only local information in link addition. Simulations under both the shortest path and efficient routing schemes verify the effectiveness of the proposed link-addition mechanism. We have found that RSH obtains increased traffic capacity compared with the existing improved efficiency (IE) link-addition strategy. In addition, the RSH strategy does not change the connectivity characteristic of the network.
When wireless transmission is performed over the bandwidth in the order of a gigahertz, high-resolution analog-to-digital converters (ADCs), and the large number of radio frequency chains ...significantly increase the power consumption. To address this issue, one promising technique is to use low-resolution, even one-bit ADCs. Another promising technique is to apply a hybrid precoding architecture to reduce the number of RF chains. In this paper, we propose to combine those techniques to reduce the hardware costs in multi-input multi-output system. Our objective is to optimize the hybrid precoder with the aim of increasing the achievable rate. To this end, we first derive an expression for the achievable rate in flat fading channels based on the Bussgang theorem, which is able to reformulate the nonlinear quantitative process as a linear function with identical first- and second-order statistics. To solve the non-convex hybrid precoding design problem, we treat the hybrid precoding design as a matrix factorization problem, which can be solved with an efficient alternating minimization algorithm. That is, we solve the digital precoder and the analog precoder in an alternative way in two separate subproblems. To find the optimal precoder in the first subproblem, we first prove the optimal structure of the digital precoding matrix. With it, we transfer the digital precoding design to a power allocation problem, the closed-form solution of which is then optimally found by using Karush-Kuhn-Tucker conditions. In the second subproblem, due to the non-convex modulus-norm constraint, it is challenging to directly solve the analog precoder. To resolve this problem, we propose to optimize the phases in the analog precoding matrix and adopt the subgradient algorithm to find the local optimal solution. Our simulation results show that the proposed hybrid precoding design effectively improves the achievable rates.
The cloud radio access network (C-RAN) has been considered as a promising network architecture to improve both spectrum efficiency and energy efficiency of current wireless networks. In this paper, ...we aim to address the channel uncertainty issue in the multi-input single-output C-RAN by studying the robust beamforming. We formulate the robust beamforming design problem with an aim to minimize the overall network power and backhaul cost while satisfying the each radio remote head power constraint and guaranteeing individual signal-to-interference-plus-noise ratio (SINR) requirements. The channel state information is assumed to be imperfect, and the additive channel state information error is modeled as Gaussian distributed variables. Formulated problem is hard to solve due to the non-convex <inline-formula> <tex-math notation="LaTeX">\ell _{0} </tex-math></inline-formula>-norm functions and channel uncertainty in the constraints. Two statistical approaches, named average approach and probability approach, are proposed to deal with SINR requirements when including the channel uncertainty. <inline-formula> <tex-math notation="LaTeX">\ell _{0} </tex-math></inline-formula>-norm approximation and a majorization-minimization algorithm are utilized to transform <inline-formula> <tex-math notation="LaTeX">\ell _{0} </tex-math></inline-formula>-norm problem into a series of semidefinite programing (SDP) problems. After that, we propose an alternating direction method of multipliers (ADMM)-based algorithm to solve each SDP problem. We introduce two auxiliary variables to reformulate the SDP problems in an ADMM form, which further ensure that solving the SDP problem can be decomposed to solve three convex subproblems. A subgradient algorithm, Karush-Kuhn-Tucker conditions, and a projected gradient method are applied to solve them, respectively. Simulation results verify that the proposed robust algorithm can significantly enhance the performance compared the non-robust case.
In this paper, complex network theory is used to generate robust scale-free topology for wireless sensor networks (WSNs). Nodes in WSNs consume energy in two stages: network generation and network ...operation. Existing scale-free models for WSNs focus on the energy in the first stage. However, sensors consume most energy in the second stage. This paper proposes a method called flow-aware scale-free (FASF) model to balance the energy consumption of sensors in the second stage. Taking into account the traffic flow in the network, a WSN is modeled as a weighted network and its energy usage is balanced. Both analysis and simulations indicate that FASF enhances connectivity and network lifetime, achieves high robustness against node failures, and at the same time maintains the scale-invariant property.
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