Vehicular edge computing (VEC) networks supporting delay-sensitive services face fundamental challenges in maintaining information freshness under high mobility, bursty task arrivals, and limited communication and computation resources. This paper investigates an Age of Information (AoI)-oriented resource allocation problem in digital twin (DT)-empowered VEC systems, where task offloading, wireless transmission, and computation scheduling are tightly coupled across time. To address the limitations of reactive and myopic optimization, we propose a DT-augmented multi-agent soft actor–critic (DT-MASAC) framework that explicitly embeds AoI dynamics and DT-based predictive features into cooperative multi-agent learning. The DT layer provides short-term foresight of channel conditions and edge resource availability, enabling agents to make proactive and uncertainty-aware decisions. A joint AoI–energy minimization problem is formulated under realistic communication, computation, and deadline constraints, and solved via centralized training with decentralized execution. Extensive simulations demonstrate that the proposed DT-MASAC framework achieves superior AoI stability and energy efficiency compared with state-of-the-art baselines, particularly in highly dynamic vehicular environments.

Ultrasonic index modulation can effectively improve the spectral efficiency and energy efficiency of intra-body communication systems. This letter proposes a codeword-based auto-correlation (C-AC) receiver for ultrasonic code-indexed modulation (UCIM) and ultrasonic time-code-indexed modulation (UTCIM) transmitters, employing Hadamard codewords. The core idea is to utilize the auto-correlation properties of the Hadamard codewords to demodulate the code index bits, where the demodulation of each code index bit is based on the sum of the dot products of every two sub-sequences, dispensing with precise synchronization and channel state information. The theoretical bit error rate (BER) is derived and verified by extensive Monte Carlo simulations over intra-body fading channels, revealing that the proposed non-coherent low-complexity C-AC receiver can achieve lower BER compared with the conventional transmitted-reference receiver for both the UCIM and UTCIM transmitters.

Wireless-powered Internet of Things networks face critical challenges due to the limited energy of sensor nodes and the difficulty of maintaining data freshness. To address these issues, this paper proposes a multi–unmanned aerial vehicle (UAV)-assisted data collection framework to minimize the age of information (AoI). A hierarchical multiple decision strategy (HMDS) is developed to optimize UAV hovering time by dynamically selecting non-orthogonal multiple access or orthogonal frequency division multiple access for intra-cluster transmission according to energy constraints and channel conditions. In addition, a multi-collaborative trajectory optimization (MCTO) scheme is proposed to reduce UAV flight time through joint clustering, partitioning, and trajectory planning. Specifically, radius-adaptive K-means++ clustering, load-balanced spectral partitioning, and a hybrid K-nearest neighbors and elite ant strategy are employed. Simulation results show that the proposed HMDS and MCTO significantly reduce hovering and flight times, thereby effectively improving AoI performance.

This paper considers a two-hop status update transmission system with energy constraints, and considers the Age of Information (AoI) of the system in multi-relay and dual-relay cases. Specially, we assumed that the arrival times of the status updates and the harvesting energy units follow a Poisson distribution, and the service time follows an exponential distribution. In the multi-relay cases, the single discrete Markov state is adopted to describe the transition between states, and the AoI in the multi-relay system is studied by using the Stochastic Hybrid System (SHS) method. In the dual-relay cases, a two-dimensional vector is constructed to represent the occupancy of the energy buffer and the relay, and the Markov process is utilized to describe the state transition of the system. Further, we derive the closed-form expressions for the Moment Generating Function (MGF) of AoI. The numerical results demonstrate the importance of obtaining the MGF of AoI in the design and optimization process of real-time status update systems.

In wireless-powered cognitive radio networks, short-packet communication has emerged as a pivotal technology for supporting Internet of Things (IoT) services due to its low-latency characteristics. However, the traditional Shannon capacity theory fails to accurately characterize the finite blocklength transmission properties of short-packet communication. Moreover, the inherent uncertainties in spectrum contention between primary and secondary users, coupled with energy harvesting in coverage-limited scenarios, further complicate the optimization of Age of Information (AoI). To address these challenges, this paper proposes a dynamic scheduling method for AoI-sensitive short-packet communication. First, based on the finite blocklength transmission theory, we derive a closed-form expression for the successful transmission probability of cognitive users’ short-packet data under interference constraints, which quantifies the impact of energy harvesting efficiency and spectrum sensing accuracy on transmission reliability. Second, we formulate a mixed-integer nonlinear programming problem to minimize the system’s expected weighted AoI, jointly optimizing spectrum access, energy allocation, and short packet encoding parameters. To solve this problem, we design a Lyapunov optimization-based maximum weight scheduling strategy, which achieves real-time decision-making by dynamically balancing data queue backlog and AoI weight factors. Simulation results demonstrate that the proposed strategy significantly outperforms round-robin and random scheduling strategies, achieving performance closer to the theoretical lower bound. Furthermore, the impact of short-packet coding length and transmission power on the system’s weighted sum AoI is thoroughly investigated.

With the rapid development of the Internet of Vehicles (IoV) and the increasing demand for real-time data processing, efficient resource allocation (RA) has become a critical challenge in vehicular edge computing (VEC) systems. In this article, we present a novel hybrid deep reinforcement learning (DRL) framework for optimizing RA in reconfigurable intelligent surface (RIS)-assisted VEC systems. The proposed framework addresses the dual challenges of minimizing the Age of Information (AoI) and maximizing energy efficiency in dynamic vehicular networks. By leveraging a hierarchical decomposition strategy, the framework separates the optimization of RIS phase shifts and federated power allocation, enabling efficient management of high-dimensional decision spaces. The upper layer employs a twin delayed deep deterministic policy gradient (TD3)-based RIS controller to optimize phase shifts, while the lower layer utilizes a federated multiagent deep deterministic policy gradient (FMADDPG) algorithm for power allocation. To enhance policy awareness and accelerate convergence, a trajectory pool of upper-layer RIS phase shifts is constructed and embedded into the lower-layer state space, thereby achieving soft-coupled collaboration among hierarchical policies. Simulation results under realistic urban mobility patterns and 3-D geometric channel models demonstrate that the proposed framework significantly outperforms benchmark algorithms, including soft actor–critic (SAC), QMIX, and block coordinate descent (BCD), in terms of AoI reduction, energy efficiency, and communication throughput.

This work focuses on an Internet of Things (IoT) status update system with the assistance of mobile edge computing (MEC) under short packet communications. The edge server includes a successive interference canceller (SIC) and a buffer pool. To simultaneously improve both information timeliness and throughput, a layer-coded hybrid automatic repeat request (L-HARQ) protocol is proposed especially considering backtrack decoding (BD) delay. In the MEC-assisted L-HARQ IoT status update system, the source successively transmits mixing updates to an access point (AP). The mixing update consists of the new generation and the part of the previously failed one. All the undecoded mixing packets are delivered to the edge server. Once a successful feedforward decoding (FD) occurs, the edge server attempts to recover undecoded mixing packets until a BD failure occurs or all buffers empty. The successful BD results are also delivered to the IR and the obtained prior information is fed back to the edge server for the next BD. By employing the stochastic hybrid system (SHS) model, the average age of informations (AoIs) are derived under circle-shift preemption (CS-P) and fixed preemption (F-P) policies. Considering the fact that the number of buffers is limited and the successful FD and BD do not always cause the reduction of system AoI, this work proposes a non-binary age evolution model as well as the state simplification mothed in SHS. The presented numerical results show that the CS-P and F-P policies obtain the enhanced information freshness compared with the non-preemptive blocking policy, and the CS-P policy outperforms the F-P one in terms of information freshness. The average AoI greatly depends on BD depth. When it is small, the average AoI is small. However, the two policies have the same average throughput that mainly depends on the size of buffer pool and the success probabilities of both FD and BD.

Reconfigurable Intelligence Surface (RIS) can improve the surrounding bad propagation environment in a controllable way, which is considered as a potential technology in future wireless communication. At the same time, Unmanned Aerial Vehicle (UAV) has also been widely used in the field of wireless communication due to its mobility, flexibility, easy deployment and low cost. With the increasing complexity of the communication environment, the transmitted confidential information can be easily intercepted by potential eavesdroppers. To deal with this dilemma, an RIS-assisted UAV secure wireless communication system was studied, which consisted of a base station (Alice), a UAV, a RIS, a passive eavesdropper (Eve), and a User. The high mobility of the UAV and the adjustable ability of the RIS were used to prevent potential eavesdroppers. The proposed system maximizes the average secrecy rate by jointly optimizing the power allocation, RIS phase shift, and UAV trajectory from a physical layer security perspective. Due to the non-convexity of this problem, this scheme decomposes this problem into three sub-problems. Firstly, the lower bounds of the power allocation and the UAV trajectory were found by applying the first-order Taylor expansion respectively, and then the successive Convex Approximation (SCA) method was used to further solve the problem iteratively. Finally, the closed-form solution of the RIS phase shift was derived. The final data results show that the proposed scheme has low computational complexity, and the average secrecy rate of the system is significantly improved compared with the benchmark scheme.

Due to the broadcast nature, wireless communications can be easily overheard by malicious eavesdroppers. In this paper, artificial noise sent by the friendly unmanned aerial vehicle (UAV)-jammer is used to weaken the eavesdropping channel from the secondary relay (SR) to the eavesdropper, in order to achieve the objective of optimizing the secrecy AoI (SAoI) of the system. With this consideration, this paper interests the SAoI of a relay cooperation system with the assistance of a UAV jammer and proposes two optimal policies. The Optimization problem is described as a joint optimization of the secondary system transmission power, the UAV transmission power and the UAV trajectory. This work designs the optimal framework that is solved with a tractable CVX tool and slack variables. Simulation results show that the UAV trajectory perform well in minimizing the AoI, and indicate that the information secrecy and freshness are simultaneously guaranteed.

Age of information (AoI) is a crucial metric to measure the information freshness in the real-time remote monitoring system. This work proposes a novel IoT status update model with the assistance of a mobile edge computer (MEC), which consists of a source (S), an access point (AP), an information receiver (IR), and the MEC with K buffers that are indexed from 1 to K. The status updates at source randomly arrive according to Poisson process of rate λ. The paper employs the layer-code Hybrid Automatic Repeat Request (L-HARQ) protocol to deal with the information freshness. The status update is decoded at the AP first. If the decoding fails, the packets are stored in the MEC buffers according to the order of increasing indexes until a successful feedforward decoding occurs. Then, the MEC performs the backtrack decoding to successively recover previously stored packets by using the L-HARQ framework. If a backtrack decoding failure occurs, the remaining ones are discarded. The backtrack decoding service at MEC follows another Poisson process with rate λB. This work employs the stochastic hybrid system (SHS) framework to derive the average AoI. At the same time, since the number of buffers is limited, this work proposes a circle-shift preemption policy to prevent packet overflow, which is the mixing packet in the (K −1)-th buffer is replaced by the one in the K-th buffer, and the new mixing packet is stored in the K-th buffer. The present numerical results validate the derivations and correctness.

Although the use of full duplex (FD) multiple relays is promising in Internet of Things (IoT) systems, this scheme has low energy efficiency. In addition, it is not known whether multi-relay cooperation is always beneficial to freshness of status update. With this, a tradeoff among age of information (Aol), throughput, and energy is designed in a FD multi-relay assisted IoT system. We first propose an earliest partial FD relay selection scheme by jointing automatic repeat request (ARQ). Secondly, the employment of ARQ causes the randomness of the retransmission numbers of the two-hop relay links and the out of order update delivery. To address this complex problem, a synchronous cooperation delivery mechanism is also integrated, where a new round of the packet transmission begins only when both the FD relays and destination successively recover the received status update. Finally, we derive the average Aol by establishing four different cases. The numerical analysis shows that the increase of the number of the selected relays is not always beneficial to the information freshness.

Considering the impact of packet reliability on the freshness of information at the wireless sensor system, this paper proposes a status update system, which consists of two sources, a common relay, and a destination. The two sources are available to deliver information to the destination. We assume that the information transmitted by one source is more reliable than the other, and the destination is more inclined to receive the information generated from the reliable sources even though it is a bit delay compared to the information generated from the unreliable sources. In this paper, we utilize the stochastic hybrid system (SHS) technique to derive the average age of information (AoI) of the reliable system with the packet management policy, in which reliable packet can preempt unreliable packet. Simulation results show that the average AoI of the reliable source is affected by the generation rate of reliable packets, the service rate of the system, and the generation rate of unreliable packets under the preemption policy.

We construct a time-sensitive wireless powered communication network (WPCN) and design scheduling policies to minimize the age of information (AoI) at mobile edge server (MES). Existing scheduling policies for AoI optimization assume that the channel between source and destination is completely reliable, or that the packet transmission success probability is constant, which is in low conformity with the real situation. We consider the unrealiable channel conditions and derive the packet transmission success probability of short packet communication (SPC) under the radio frequency power supply constraints, and frame the expected weighted sum AoI (EWSAoI) optimization problem. Finally, when considering the time-varying packet transmission success probability, stochastic arrival and queuing rules of packets, we design stationary randomized scheduling policy and Max-weight scheduling policy to optimize the EWSAoI. The simulation results demonstrate that the EWSAoI of the Max-weight scheduling policy is closest to the theoretical lower bound. In addition, since the channel between sensor and MES is unreliable, the SPC coding parameters and transmission power of wireless power station (WPS) have important effects on EWSAoI by changing packet transmission success probability.

Remote monitoring systems heavily rely on the Age of Information (AoI) as a critical metric to gauge the timeliness of status updates received by a destination. Presently, the predominant focus of AoI evaluations in sensor networks revolves around communication systems employing homogeneous preemption, often neglecting the issue of packet loss. Consequently, our research directs attention towards the single-buffer state update system featuring non-homogeneous preemption in scenarios involving packet dropping. This system entails a wireless communication network comprising three distinct components: a buffer, a server, and a destination node, each generated following the Poisson process and subsequently encapsulated into brief packets for transmission by the server. Initially, a diverse source buffer preemption strategy was employed, wherein packets of higher priority consistently superseded those of lower priority in the buffer, and packets originating from the same source were preempted in the buffer, resulting in the direct discarding of preempted packets. Subsequently, we compute the average Age of Information (AAoI) for diverse sources by leveraging Stochastic Hybrid System (SHS) methodologies to manage packet priorities. Ultimately, system simulations and numerical assessments unveil that with a 0.2 probability of detecting update packets, the AoI diminishes by 23.9% as the Signal-to-Noise Ratio (SNR) escalates from 30 dB to 60 dB. Holding the SNR constant at 60 dB while extending the packet length for status updates from 200 to 600 bits results in an average AoI reduction of 14.5%.

This paper focuses on the timely delivery of status updates for a multi-relay assisted energy harvesting (EH) Internet of Things system with short packet communications (SPC), where an EH-powered source transmits status updates to a destination with the aid of multiple EH-powered relays. To improve the energy efficiency and information freshness, an earliest-$\ell $partial relay selection scheme is proposed, in which the earliest$\ell $relays that successfully receive the status update from the source will be selected to forward the status update to the destination, and the selection combining (SC) and maximal-ratio combining (MRC) schemes are used at the destination. Firstly, we investigate the update packet delivery schemes of source-relay (S-R) and relay-destination (R-D) links, and present the packet error probabilities under the SC and MRC schemes based on SPC theory. Secondly, after characterizing the full charge time durations of both the source and relay, we investigate the statistical description of the number of the packet transmission attempts from the source to relay as well as the one from the relay to destination by using order statistics. With the analysis of the evolution of the instantaneous age of information (AoI), the expression for average AoI is derived. Finally, we investigate the average AoI minimization, which is formulated as a coupled triplet problem of the packet lengths at the source and relays and the value of$\ell $. To overcome the coupling, we present the convexity approximation of the average AoI as well as the concise proof. Then, an efficient gradient-based two-step optimal search algorithm is proposed to solve the optimization problem, which searches the local optimal packet lengths for S-R and R-D links by iteratively updating the value of$\ell $until the global optimal objective parameters are found. Numerical analyses give the effect of the key parameters on the average AoI, and the comparison demonstrates that the proposed gradient-based method converges quickly than the conventional greedy search method.

This paper studies the age of information (AoI) and its distributional properties for a dual-source status update system with transmitters characterized by energy constraints. Specially, the two sources send their sensed measurements in the form of status updates to the destination through a server powered by energy harvesting (EH). Meanwhile, arrivals times of the status update packets and the harvesting energy units at the transmitter are assumed to be random according to independent Poisson processes. The service time of each packet is assumed to be exponentially distributed. Firstly, we construct a three-dimensional state vector to track the occupancy of energy buffer, server and data buffer. Furthermore, by describing a multi-dimensional random process of AoI evolution representing all possible state transitions of the system, we could use the stochastic hybrid system (SHS) to characterize the moment generating function (MGF) of AoI. Therefore, we further derive closed-form expressions for the first and second moments of AoI by solving the differential equations. The numerical results illustrate that in the design and optimization process of the dual-source sensor status update system, it is necessary to incorporate the second-order moment and even higher-order moments of AoI.

Ultrasonic intra-body communication (IBC) is an emerging technique to enable revolutionary healthcare applications. This paper proposes an ultrasonic index modulation with spread spectrum (UsIM-SS) scheme for IBCs. The information bits consist of modulation bits and index bits. The core idea of UsIM-SS is that the modulation bits are spread by spreading codes and the index bits are leveraged to select the time-hoping sequence to transmit the spreading bits. We also find that the existing ultrasonic wideband (UsWB) and UsIM can be regarded as special cases of the proposed UsIM-SS. Furthermore, the soft decision-based maximum likelihood (S-ML) receiver and hard decision-based ML (H-ML) receiver are proposed for UsIM-SS, providing a trade-off between bit-error rate (BER) and complexity. Theoretical spectrum efficiency (SE) and BER expressions for UsIM-SS using S-ML and H-ML are also derived and verified by extensive Monte Carlo simulations. Both theoretical and simulation results show that UsIM-SS can achieve lower BER and higher SE than existing UsWB and Us 1M techniques.

This article presents a dual-bandwidth front-end (FE) for a rapidly reconfigurable dual data rate and power-proportional optical receiver. The proof-of-concept receiver FE is capable of operation at 8- and 4-Gb/s data rates. Implemented in 65-nm CMOS technology, the proposed FE consists of a shunt-feedback transimpedance amplifier (TIA), a configurable one-stage-to-three-stage postamplifier (PA), and an offset compensation (OC) loop. By reconfiguring the number of stages in the PA, the FE maintains a near-constant delay when its bandwidth is changed. This allows synchronization to be maintained, with limited bit errors when the target data rate is switched. The prototype receiver was measured with an optical input at 8 and 4 Gb/s. The overall FE dissipates 6.12 mW at 8 Gb/s (0.76 pJ/bit) and 2.86 mW at 4 Gb/s (0.72 pJ/bit). The measured receiver optical sensitivities for 8- and 4-Gb/s inputs at high-bandwidth (HBW) and low-bandwidth (LBW) modes are −7.7 and −9.8 dBm, respectively. The measurement results confirm the matched delay through the FE with delay variations within 8 ps.

In this paper, we study the age of information (AoI) for a sensor network with practical non-linear energy harvesting (NEH) and outdated channel state information (CSI). Specifically, we study a simple relay assisted network model, where the relay system uses amplify and forward (AF) protocol, the energy-limited sensor source harvests energy from the radio frequency (RF) signal of the relay that is connected to fixed energy source. We assume that the channel model follows the Rayleigh fading. Based on these, we drive the end-to-end block error probability, we also give mathematical expressions for the statistical descriptions of the time duration for the sensor fully recharging and the closed-form expression of the average AoI. The numerical results show the influence of parameters of NEH and outdated CSI.

For the multi-access channel wireless sensor network scenario with limited channel resources, the transmission of real-time information needs to consider the channel environment and the freshness of information. This paper studies the multi-access heterogeneous sensor cognitive radio network, the secondary user (SU) shares the primary user (PU) spectrum through the underlay scheme, considering the stability of the data queue in the SU, the working state of the PU and the stability of service interference constraints, an optimization problem that minimizes the average AoI of EH nodes is proposed. Then, the AoI optimization problem is solved by jointly optimizing the data arrival probability and the energy arrival probability using a distributed probabilistic access (PA) policy, in which two SU nodes make independent transmission decisions according to corresponding probability distributions. The simulation results show that the transmit power of the PU will also affect the average AoI under the constraint of PU stable service interference.

In this paper, we study the average age of information (AoI) in energy harvesting wireless sensor networks with preemptive transmission. The downlink control signal is transmitted to sensors for allocating wireless resource with ARQ, and two sensors synchronously harvest energy and send the sampled common data to a base station (destination) with truncated HARQ-MRC. Firstly, the energy state transition diagram is characterized by a Markov chain and the construction method of energy transition matrix is introduced. Then, the expression of average AoI is derived for the preemptive transmission. Lastly, numerical results are provided to evaluate the energy and AoI performance of dual-sensor status update systems.

Age of information (AoI) is a new performance index proposed recently, which is used to describe the freshness of information. This paper studies$A$oI minimization for the unmanned aerial vehicle (UAV)-assisted cognitive radio networks (CRN), where the primary users and secondary users share the authorized spectrum, and UAV as a relay adopts time division duplex (TDD) scheme for uplink and downlink transmissions. We focus on AoI minimization by jointly optimizing the UAV flight trajectory and resource allocation. Since the optimization problem is non-convex, we use an efficient successive convex approximation iterative algorithm to solve the optimal solution, while satisfying the conditions of interference threshold and feasibility constraints. Simulation results show that the proposed joint design scheme can effectively improve the freshness of information.

The irregular distribution of drones in space poses great challenges to the design and deployment of the networks. In this paper, we use point process theory and stochastic geometry model to develop a drone heterogeneous network (HetNet) framework. In order to better reflect the real scene, we assume that the macro base stations are two-dimensionally distributed on the ground, while the drones as small base stations are three-dimensionally distributed in the air. We assume that the channel model follows the Nakagami-m fading, and the user is associated with the base station by the maximum bias received power (Max-BRP), which is necessary to reduce the pressure on the terrestrial macro base station. Based on these, we give mathematical expressions for the association probability and outage probability between the user and each base station. The numerical results show that the proposed hybrid modeling method can better capture the actual base station deployment. In the ultra-dense drone network, setting an appropriate bias factor can effectively relieve the pressure of the macro base station and improve the network performance.

Age of information (AoI) and energy efficiency (EE), as two important performance metrics in status update systems, usually cannot be simultaneously optimized. This paper investigates the age and energy tradeoff for multicast networks with retransmissions, where each sensed status update is encoded as a short blocklength packet and is broadcasted to multiple destinations via independent and identically distributed error-prone channels. By considering the stopping threshold, the average AoI and EE expressions for stopping at earliest-l, stopping at preselected-l, and wait-for-all schemes are derived as a function of the packet length. On this basis, the average AoI-EE ratio is introduced and is minimized to trade off age and energy by optimizing the packet length. Numerical results indicate that among the three schemes, earliest-lscheme attains the minimum AoI when the packet length is small, and preselected-lscheme attains the maximum EE when the packet length is large. An optimal packet length can always be found for each scheme to minimize age-energy ratio. Moreover, the selection of stopping thresholdlwill also impact the age and energy performance.

This paper presents a source-synchronous receiver architecture for use in parallel optical links. The proposed system is reconfigurable, allowing any channel to be used as a clock or data lane. The architecture is designed for modedivision multiplexed (MDM) optical links with forwarded clocks and allows the sensitive clock signal to be placed in the lane with the least amount of optical crosstalk for a given photonic interconnect. This configurability, which accounts for variation in integrated optics by leveraging the more robust electronic chip, optimizes the performance in electronic/optic codesigned solutions and may improve the yield. The architecture contains a dynamic clock distribution network, able to send a reference clock signal from the chosen clock receiver to any other data-configured receiver. The proposed architecture has been implemented on an experimental chip consisting of two receivers designed in the 65-nm CMOS technology. Electrical measurements at 8 Gb/s were done, and bit error rate curves are presented. They demonstrate the ability to swap and repurpose the clock and data inputs between the receivers, with similar sensitivity upon reconfiguration as a proof of concept.

This paper explores the potential of physical layer security for K- tier heterogeneous networks (HetNets) with nonbest user association (UA) scheme. By modeling the spatial positions of network elements in each tier as homogeneous Poisson point processes (PPPs), we first present the non-best UA probability of a typical user equipment associating with the m-th average biased received power (ABRP) with passive eavesdroppers, then the expression of total secrecy probability for the K-tier HetNets is derived with stochastic geometry. Both the analytical and numerical results show that the implementation of the non-best UA scheme can significantly improve the secrecy probability, which indicates that non-best UA could be a promising solution for safeguarding K-tier HetNets. Moreover, we show that the secrecy probability with non-best UA scheme is not always decreasing over the transmission power of the base stations, which is quite different from the best ones.

In order to enhance simultaneously the association robustness of mobile users and spectrum efficiency (SE) of systems, by integrating the decoupled uplink (UL)/downlink (DL) association (DUDA) and cross‐tier dual connectivity (DC), the orthogonal multiple access (OMA)‐mode and non‐OMA (NOMA)‐mode design schemes are investigated over a three‐tier heterogeneous network (HetNet) accompanying with the proposition of a conditional association analysis method. The scheme exploits effectively the DC requirement of NOMA. Additionally, in the proposed conditional association design and analysis method, the decoupling UL association designs are conducted only under a given DL association condition. Owing to low complexity, this method shows that it is very easy to achieve the possible decoupling UL DC designs and the corresponding condition association probabilities. Then, the conditional coverage probabilities and SEs of the OMA‐mode and NOMA‐mode HetNets are derived by specially considering DUDA and coupled UL/DL association strategies. The proposed conditional design framework can be easily extended to multi‐tier HetNets and is helpful to select feasible DL candidate from all possible DL associations so that the resulting UL associations are optimal. Besides this, the cross‐tier DC design ensures the effective exploitation of the whole network resources because different tiers have different serving levels.

This paper presents a source-synchronous receiver architecture for use in parallel optical links. The proposed system is reconfigurable, allowing any channel to be used as a clock or data lane. The architecture is designed for mode-division multiplexed (MDM) optical links with forwarded clocks and allows the sensitive clock signal to be placed in the lane with the least amount of optical crosstalk for a given photonic interconnect. This configurability, which accounts for variation in integrated optics by leveraging the more robust electronic chip, optimizes the performance in electronic/optic codesigned solutions and may improve the yield. The architecture contains a dynamic clock distribution network, able to send a reference clock signal from the chosen clock receiver to any other data-configured receiver. The proposed architecture has been implemented on an experimental chip consisting of two receivers designed in the 65-nm CMOS technology. Electrical measurements at 8 Gb/s were done, and bit error rate curves are presented. They demonstrate the ability to swap and repurpose the clock and data inputs between the receivers, with similar sensitivity upon reconfiguration as a proof of concept.

A novel m th best average biased received power (ABRP) user association (UA) scheme is proposed for K ‐tier heterogeneous networks, where a user is associated with the closest base station (BS) of the k th tier having the m th strongest ABRP, . By using stochastic geometry and Poisson point processes, the authors perform the analysis of the UA probability that a typical user is associated with a BS that has the m th strongest ABRP as well as the downlink signal‐to‐interference‐noise ratio (SINR) coverage performance. The obtained results show that, for a given tier k , when the layer's position in the ordered set of ABRPs is not equal to m and the power or density of BSs is relatively small, i.e., , the UA probability increases monotonically with or . Contrarily, it decreases. For the other UA probabilities, the opposite results are achieved. Additionally, the results also show that the coverage probability of the downlink SINR of the tier k always increases with power , which is consistent with the one in the conventionally best ABRP scheme. However, for other tiers, the corresponding downlink SINR coverage probabilities do not behave monotonically with the power .

This paper presents a transceiver for a long on-chip link in 130-nm CMOS. It features a hybrid-mode transmitter with a current sense amplifier receiver. From the perspective of power efficiency, voltage-mode pre-emphasis is preferred because it reduces the current consumption of the circuit. Based on simulations, an on-chip link in 130-nm CMOS achieves 8 Gb/s over 5-mm long interconnects, while consuming 256 fJ/bit corresponding to 51.2 fJ/bit/mm with 1.2 V supply.

This paper focuses on a multi‐user full‐duplex massive multiple‐input multiple‐output amplify‐and‐forward relaying system with low‐resolution analogue‐to‐digital convertors (ADCs). By modelling the loop‐interference and quantisation noise as additive noise, we perform the analyses of the achievable spectral efficiency (SE) by considering the two canonical processing schemes, maximum ratio combining/maximal ratio transmission (MRC/MRT) and zero‐forcing receive/zero‐forcing transmission (ZFR/ZFT), respectively. Specially, we first obtain the tractable closed‐form expressions of the achievable SE. Then, we present the asymptotic analyses under three different power‐scaling scenarios. Comparison analysis shows that the low‐resolution quantisers impose more performance loss on ZFR/ZFT schemes than MRC/MRT ones. At the same time, it is found that with different power‐scaling schemes, the systems have different capabilities to restrict the effect of loop interference and low‐resolution ADCs. Specially, the impact of both the loop‐interference and quantisers on achievable SE can be restricted effectively only under the power‐scaling scenario where the relay's transmission power is scaled down with the number of transmit antennas and the sources’ transmission power is fixed. For the power‐scaling case where the transmission powers of both relay and sources are scaled down simultaneously with the number of antennas, only the effect of the loop interference can be restricted, but the one of low‐resolution quantisers remains.

To obtain an insight about the effect of channel parameters on buffer‐aided relay selection systems, the max‐link selection (MLS) schemes are investigated over independent and non‐identically distributed (i.ni.d) Rayleigh fading channels. Specially, by employing Markov chain, the authors first model the state transition matrix and outage probability. Secondly, they obtain the closed‐form expressions of the corresponding statistic properties. The presented results show: (i) when the relaying channels are asymmetric (but the source–relay links are independent and identically distributed fading, so does the relay–destination links), the MLS scheme outperforms the traditional best relay selection (T‐BRS) and max–max best relay selection (MM‐BRS) schemes. However, when the relaying links are unbalanced severely, the MLS scheme does not provide diversity gain over the T‐BRS and MM‐BRS schemes; and (ii) For the more general i.ni.d fading case, it is observed that the MLS schemes can be inferior to the MM‐BRS schemes. The derivations of this work have values for reference. For example, by using the achieved statistic properties they can further perform the investigation on the delay for the buffer‐aided MLS relaying systems over i.ni.d fading channels, which is a critical issue of buffer‐aided relay selection systems.

In the existing literature about cognitive radio opportunistic relaying (CR‐OR) systems, the first‐order statistics such as outage probability are investigated widely. However, for the second‐order statistics, such as average outage duration (AOD) and average outage rate (AOR), there is not open works, still. To obtain a comprehensive cognition on the behaviour of mobile communication systems, this study focuses on the second‐order statistical properties of CR‐OR systems. There are two CR‐OR schemes considered, in which the canonical amplify‐and‐forward (AF) and reactive decode‐and‐forward (RDF) are employed, respectively. Since the equivalent end‐to‐end signal‐to‐noise ratio (SNR) of AF CR‐OR is complicated such that it is very difficult to obtain the closed‐form solution to AOR of AF CR‐OR schemes, the high SNR approximation in AF CR‐OR schemes is employed. For the two schemes, first the closed‐form solutions to AORs and AODs are obtained by using appropriate mathematical proof. Based on the derivations, the comparison analyses about AORs and AODs of the two schemes are provided. The comparison results show that, under high SNR approximation, the AF CR‐OR scheme achieves the same AOR and AOD as RDF CR‐OR. Finally, the impact of system parameters on AORs and AODs is provided.

To overcome the performance loss caused by the N th single best relay selection schemes, in this study, the authors present the N–R th dual best relays selection schemes. In the proposed schemes, there are two relays selected out of the available relays to forward the received signals to the destination by using the decode‐and‐forward protocol. The statistical descriptions of instantaneous end‐to‐end received signal‐to‐noise ratios (SNR) are investigated over independent and non‐identically distributed Nakagami‐ m fading channels. By using the appropriate mathematical proof, the authors firstly obtain the closed‐form expressions to the probability density function and cumulative distribution function of instantaneous end‐to‐end SNR. Then, based on the derived results, the outage probability and average symbol error rate (SER) of the proposed N–R th dual best relays selection schemes are investigated. The comparison analyses between the N th schemes and the N–R th schemes show that the proposed N–R th dual best relays selection schemes can improve greatly the performance of opportunistic relaying systems such as outage probability and average SER. Especially, the proposed dual best relays selection scheme can obtain more outstanding improvement on SER.