In this letter, we derive an approximate analytical expression for the uplink achievable rate of a massive multiinput multioutput (MIMO) antenna system when finite precision analog-digital converters (ADCs) and common maximal-ratio combining technique are used at receivers. To obtain expression, treat quantization noise as additive model. Considering obtained show that low-resolution ADCs lead to decrease in but performance loss can be compensated by increasing number receiving antennas....

Machine (deep) learning-enabled accurate traffic modeling and prediction is an indispensable part for future big data-driven intelligent cellular networks, since it can help autonomic network control management as well service provisioning. Along this line, paper proposes a novel deep learning architecture, namely Spatial–Temporal Cross-domain neural Network (STCNet), to effectively capture the complex patterns hidden in data. By adopting convolutional long short-term memory its...

With accurate traffic prediction, future cellular networks can make self-management and embrace intelligent efficient automation. This letter devotes itself to citywide prediction proposes a deep learning approach model the nonlinear dynamics of wireless traffic. By treating data as images, both spatial temporal dependence cell are well captured utilizing densely connected convolutional neural networks. A parametric matrix based fusion scheme is further put forward learn influence degrees...

Exploiting unmanned aerial vehicles (UAVs) as flying relays is becoming an indispensable strategy to assist terrestrial cellular networks enhance coverage. One challenging problem for UAV-integrated how design their deployment and association schemes provide on-demand coverage with minimum network power consumption. In this paper, the uplink transmission in a UAV-assisted studied objective of minimizing transmit consumption users UAVs through designing proper UAV schemes. To avoid...

Smart cities demand resources for rich immersive sensing, ubiquitous communications, powerful computing, large storage, and high intelligence (SCCSI) to support various kinds of applications, such as public safety, connected autonomous driving, smart health, living. At the same time, it is widely recognized that vehicles, equipped with significantly SCCSI capabilities, will become in future cities. By observing convergence these two trends, this article advocates use vehicles build a...

Geometry and magnetic relaxation modulations in a series of mononuclear dysprosium complexes, [DyLz2(o-vanilin)2]·X·solvent (Lz = 6-pyridin-2-yl-[1,3,5]triazine-2,4-diamine; X Br- (1), NO3- (2), CF3SO3- (3)), were realized by changing the nature counter-anion. The DyIII ions all complexes are eight-coordinate approximate D4d symmetry environments. anisotropy these systematically investigated, both experimentally from ab initio calculations. All exhibit excellent single-molecule behavior....

Reconfigurable intelligent surface (RIS) has emerged as a promising technique for future wireless communication networks. How to reliably transmit information in RIS-based system arouses much interest. This paper proposes reflecting modulation (RM) scheme communications, where both the patterns and signals can carry information. Depending on that transmitter RIS jointly or independently deliver information, RM is further classified into two categories: mapped (JRM) separately (SRM). JRM SRM...

In this letter, we propose a task offloading framework for UAV-enabled MEC networks, where all smart mobile devices are scattered randomly following an arbitrary distribution. By exploiting the hovering and mobilizing capability of UAV, service can be provided to in sub-areas network. To extend UAV operating time associated network lifetime, formulate optimization problem minimize total energy consumption through joint region partitioning trajectory scheduling. solve it, decompose it into...

Vehicle-to-vehicle communications can offer direct information interaction, including security-centered and entertainment information. However, the rapid proliferation of vehicles diversity services demand for a more intelligent efficient resource allocation framework to enhance network performance. In this article, multi-agent deep reinforcement learning-based is developed jointly optimize channel power control satisfy heterogeneous Quality-of-Service (QoS) requirements in vehicular...

Reconfigurable intelligent surface (RIS) provides a promising way to build the programmable wireless transmission environments in future. Owing large number of reflecting elements used at RIS, joint optimization for active beamforming transmitter and passive reflector RIS is usually complicated time-consuming. To address this problem, article proposes low-complexity algorithm based on fractional programing (FP). Specifically, we first consider RIS-aided multi-user communication system with...

With the development of computation-intensive applications, unmanned aerial vehicle (UAV)-enabled multi-access edge computing (MEC) provides task offloading service for users with or without terrestrial infrastructure support. Meanwhile, next generation UAVs communication systems are expected to be user-centric. Therefore, more attention should paid users' satisfaction offered service. In this paper, we study satisfaction-oriented and UAV scheduling problem UAV-enabled MEC networks, where...

This paper investigates the energy efficient downlink transmission in distributed massive multiple-input-multiple-output systems, where antennas are clustered on geographically remote radio heads (RRH). A closed form of ergodic achievable rate is derived for a specific RRH-user association and imperfect channel state information to assist formulation its system efficiency (EE). By assuming minimum user requirements practical power consumption model including both transmit antenna circuit...

Unmanned aerial vehicle (UAV) carried base stations can provide on-demand deployment for ground users. Given a target area to be serviced, this letter proposes three-dimensional (3D) method multiple UAVs based on the knowledge of statistical user position information maximize total network throughput. The 3D problem is divided into horizontal and vertical problem. Specifically, virtual force field built distributions help model communication demand Based that, placement scheme each UAV...

This work investigates proactive edge caching for device-to-device (D2D)-assisted wireless networks, where user equipment (UE) can be selected as nodes to assist content delivery reduce the transmission latency. In doing so, there are two challenges: 1) how precisely get user's preference cache proper contents at UEs and 2) replace cached when new popular emerging. To address these, we develop a learning-based (UPL-PEC) strategy. strategy, first propose novel context social-aware learning...

Along with the deployment of Industrial Internet Things (IIoT), massive amounts industrial data have been generated at network edge, driving evolution edge machine learning (ML). But during ML model training, it may bring privacy leakage by traditional central methods. To address this issue, federated (FL) has proposed as a distributed framework for training global without uploading raw to protect privacy. Since communication and computing resources are usually limited in IIoT networks, how...

Communication and sensing are two important features of connected autonomous vehicles (CAVs). In traditional vehicle-mounted devices, communication modules exist but in an isolated way, resulting a waste hardware resources wireless spectrum. this paper, to cope with the above inefficiency, we propose vehicular behavior-aware integrated (VBA-ISAC) beamforming design for transmitter multiple antennas. work, beams steered based on behaviors assist driving meanwhile provide spectral-efficient...

To improve power efficiency in vehicle-to-roadside infrastructure (V2I) communication networks, this paper proposes a joint and sub-carrier assignment policy under delay aware quality of service (QoS) requirements. Due to the real-time nature V2I transmissions, proposed should satisfy QoS requirements with minimized consumption. In particular, we develop cross-layer framework which orthogonal frequency division multiplexing (OFDM) is employed at physical layer works data link layer. Under...

This paper studies the joint transceiver design and power splitting (JTDPS) for a downlink multiuser multiple-input multiple-output (MU-MIMO) simultaneous wireless information transfer (SWIPT) system. Aiming to minimize transmit by jointly optimizing transmitter at base station, (PS) factors, decoding receivers mobile stations (MSs) subject both predefined mean-square error (MSE) given energy harvesting (EH) constraints. The formulated problem is nonconvex JTDPS optimization problem, which...

This paper focuses on the secure transmission of wireless-powered full-duplex (FD) relay systems, where a multiantenna source communicates with single-antenna destination help FD in presence eavesdropper. It is assumed that wireless energy harvesting-enabled, adopting both transmit and receive antennas to harvest time switching (TS) mode. As objective this maximize system secrecy rate through jointly designing beamforming vector, information vector TS coefficient, an optimization problem...

This letter investigates the downlink achievable rates of massive multiple-input-multiple-output (MIMO) enabled simultaneous wireless information and power transfer (SWIPT) systems. Since transmission range MIMO SWIPT systems is quite short, channels are generally line-of-sight. Therefore, by assuming Rician fading channels, this theoretically derives approximate expressions harvested energy rate. In addition, corresponding asymptotic presented for large number transmit antennas case....

This paper investigates the generic signal shaping methods for multiple-data-stream generalized spatial modulation (GenSM) and quadrature (GenQSM). Three cases with different channel state information at transmitter (CSIT) are considered, including no CSIT, statistical perfect CSIT. A unified optimization problem is formulated to find optimal transmit vector set under size, power, sparsity constraints. We propose an optimization-based (OBSS) approach by solving directly a codebook-based...

Recurrent neural network (RNN) based models are widely adopted to capture temporal dependencies in the state-of-the-art approaches for cellular traffic prediction. However, RNN is inefficient and incapable of capturing long-range data. Besides, its inherent sequential nature makes it time consuming dependencies. To better long-term dependency reduce consumed data prediction, we propose a time-wise attention aided convolutional (TWACNet) structure In proposed TWACNet, mechanism (CNN) spatial...