Journal of Communications and Information Networks
Print ISSN 2096-1081 CN 10-1375/TN
Editor-in-Chief: Wei Zhang
The performance of wireless communication systems is fundamentally constrained by the random and uncontrollable wireless channel. By leveraging the recent advances in digitally-controlled metasurface, intelligent reflecting surface (IRS) has emerged as a promising solution to enhance the wireless network performance by smartly reconfiguring the radio propagation environment. Despite the substantial research on IRS-aided communications, this article addresses the important issue of how to deploy IRSs in a wireless network to achieve its optimum performance. We first compare the two conventional strategies of deploying IRS at the side of base station or users in terms of various communication performance metrics,and then propose a new hybrid IRS deployment strategy by combining their complementary advantages. Moreover,the main challenges in optimizing IRS deployment as well as their promising solutions are discussed. Numerical results are also presented to compare the performance of different IRS deployment strategies and draw useful insights for practical design.
Nowadays, cloud computing has been identified as new opportunities for migrating to the expected agility, reuse, and adaptive capabilities that can support the ever changing IT trends and requirements. Unfortunately, the rapid evolution of those technologies also comes with open issues such as security, privacy, integrity,quality of services,and their possible detrimental consequences. In this work, the concept of insurance is introduced to compensate the cloud computing customers when encountering those failures if service providers (SPs)have insurance purchased.Particularly,we consider the situation when the insurer is unable to see the system failure risk levels of the SPs, which is usually seen as an incomplete information market, in contrast with the optimal situation in a complete information market. First, an insurance-based cloud computing architecture is proposed to build a monetary credit system in which the cloud computing SP pays a premium for a certain coverage to the insurer. Subsequently, problem is formulated to solve the optimal insurance plan in complete and incomplete information markets,together with detail analysis of insurance policies in both cases are provided. Furthermore, simulation results show the properties of the two insurance plans and parameters that affect the design of the insurance plan.
With the explosive growth of interconnected smart devices and sensors,the Internet has been entering the Internet of things(IoT)era and revolutionizing many aspects of our daily life. Meanwhile, crowdsourcing has been considered as a promising technology to realize collaborative intelligence. Therefore, more and more IoT-based crowdsourcing applications are emerged to take advantages of the widely distributed IoT devices to sense, collect, and analyze data with the aim to solve complex and nontrivial tasks. However,there exist many technical challenges to be addressed in the IoT-based crowdsourcing, such as security, privacy, and incentive provision. In this paper, we propose a blockchain-based architecture as an integrated solution to realize the secure and trustworthy crowdsourcing in wireless IoT. We first overview the challenges in the traditional crowdsourcing system. Then, we briefly introduce the background of the blockchain and smart contract, and propose a blockchain-based crowdsourcing architecture. In particular, we elaborate the utilization of smart contract on the specific phases of crowdsourcing. By deploying the smart contract instance, we confirm the proposed blockchain-based architecture is feasible.
Orthogonal frequency division multiplexing (OFDM) waveform is promising to converge communications and sensing functionalities for future wireless applications. This paper presents a novel method to improve the OFDM-based sensing accuracy by estimating the delay/Doppler leakages in the channel matrix, which is constructed by the received and the transmitted OFDM symbols. Both simulation and proof-of-concept experiment validate the proposed method for sensing improvement.The experiment uses a heterodyne W-band system at 97 GHz to transmit and receive an OFDM waveform of bandwidth 3.9 GHz.We achieve an improvement in sensing accuracy by an order of magnitude which is significant for OFDM-based converged systems.
To better support the emerging vehicular applications and multimedia services,vehicular edge computing(VEC)provides computing and caching services in proximity to vehicles, by reducing network transmission latency and alleviating network congestion. However, current VEC networks may face some implementation challenges, such as high mobility of vehicles, dynamic vehicular environment,and complex network scheduling. Digital twin, as an emerging technology, can make the virtual representation of physical networks to predict, estimate,and analyze the real-time network state. In this paper, we integrate digital twin into VEC networks to adaptively make network management and policy schedule. We first introduce the framework of VEC networks and present the key problems in a VEC network.Next,we give the concept of digital twin and propose an adaptive digital twin-enabled VEC network. In the proposed network, digital twin can enable adaptive network management via the two-closed loops between physical VEC networks and digital twins. Further,we propose a digital twin empowered VEC offloading problem with vehicle digital models and road side unit (RSU) digital models. A deep reinforcement learning (DRL)-based offloading scheme is designed to minimize the total offloading latency. Numerical results demonstrate the effectiveness of the proposed DRL-based algorithm for VEC offloading.
In this paper, we propose a preamble-based medium access control (P-MAC) mechanism in Ad-Hoc network.Different from traditional carrier sense multiple access(CSMA)in Ad-Hoc network,P-MAC uses a much shorter preamble to establish the network. First, we propose the P-MAC mechanism to shorten the time of establishing the Ad-Hoc network. Based on the P-MAC, we propose a more efficient way to maintain the network. Next, focusing on the power line communication (PLC) network which is a kind of Ad-Hoc network,we propose a frequency division power line communication (FD-PLC) network architecture to obtain the best communication frequency. To obtain the best frequency, i.e., highest signal-to-noise ratio (SNR), we design the frequency sweeping mechanism which can determine the frequency of uplink and downlink communication before the transmitter and receiver communicate. Due to the large-scale networks in industry,P-MAC can be exploited to speed up the establishment of the Ad-Hoc PLC network. Finally, we compare our mechanism with CSMA. Numerical results indicate that our strategy greatly shortens the time of establishing the Ad-Hoc network.
We study a downlink non-orthogonal multiple access (NOMA) system, in which a base station (BS) serves a near user and a far user on the same frequency band simultaneously. Due to physical obstacles or heavy shadowing, there is no direct link from the BS to the far user and the near user acts as a cooperative relay for the far user by adopting the simultaneous wireless information and power transfer (SWIPT) technique. In particular, we first derive the outage probabilities of the SWIPT-assisted cooperative NOMA system by considering both full-duplex and half-duplex relaying modes. Then, we analyze the approximated closed-form expression of exact outage probability by applying the Gaussian-Chebyshev quadrature formulas. Simulation results validate the correctness of the theoretical analysis and demonstrate the advantages of the SWIPT-assisted cooperative NOMA system over orthogonal multiple access(OMA)benchmarks.
In this paper, a novel anti-interference direction finding(DF)method for amplitude comparison method based on cyclostationarity is proposed. With the periodic properties of the communication signals, the desired signal’s amplitude value can be effectively obtained even though there is an interference signal whose frequency spectrum overlaps with the desired signal in the environment,and the corresponding incident angle can be estimated accurately with the amplitude comparison method. The influence of interference signal on the amplitude comparison method is discussed and the proposed method’s theoretical feasibility is also analyzed. Compared with the conventional method,simulations are provided to demonstrate the anti-interference capability of the proposed method. The amplitude comparison DF system working at 2.44 GHz and 5.8 GHz is also constructed to verify its feasibility.
Mobile-edge computing (MEC), enabling to offload computing tasks on mobile devices towards edge servers, can reduce the terminals cost. However, a single MEC sever usually has limited computing capabilities, which can not meet a large number of terminals’ requirements. In this paper, we consider an ultra-dense networks (UDN) scenario where the macro base stations (MBSs) are assisted by MEC severs. In particular, we first construct system model for MEC assisted UDN,and build the system overhead minimization. Next, in order to solve the problem, we transform the problem into three sub-problems,i.e.,offloading strategies subproblem, channel assignments subproblem, and power allocation subproblem. Then, employing joint offloading and resource allocation algorithms,we obtain the optimal joint strategy for the MEC assisted UDNs. Finally,simulations are conducted to evaluate the performance of our proposed algorithms. Numerical results show that obtained algorithms can effectively reduce the energy consumption of the system and improve the overall performance of the system.
