We introduce a lightweight, multi-stage framework called Correlation-Enhanced CSI Sampling (CESS) to address this challenge. CESS combines full-slot channel interpolation, inter-slot CSI processing to close the temporal measurement gap, and intra-slot subcarrier processing to mitigate frequency-domain correlation issues. Through simulations, we compare CESS to a conventional PLKG baseline, showing that CESS substantially lowers the Key Disagreement Rate (KDR) and boosts the effective Key Generation Rate (KGR), with a minimum KGR of 3.5 kbps. These results underscore CESS’s potential for secure and reliable PLKG in real-world 5G TDD systems.

This paper investigates the potential of Non-Terrestrial Networks (NTNs) as a resilient complement to terrestrial 5G/6G infrastructure in Singapore. It focuses on scenarios where terrestrial networks are unavailable, such as during nationwide outages. Through link budget analysis and antenna modeling, the study evaluates the capabilities of High-Altitude Platforms (HAPs), Very Low Earth Orbit (VLEO), and Low Earth Orbit (LEO) satellites. The findings indicate that HAPs are well-suited for urban environments due to their compact antenna requirements and favorable beam characteristics, while VLEO and LEO systems provide wider coverage, making them ideal for maritime applications. The analysis offers insights into system design, cell sizing, and interference mitigation, supporting the integration of NTNs into future communication networks.

We consider a wireless networked control system (WNCS) with imperfect bidirectional links for real-time applications such as smart grids. To maintain the stability of WNCS, captured by the probability that plant state violates preset values, at minimal cost, heterogeneous physical processes are monitored by multiple sensors. This status information, such as dynamic plant state and Markov Process-based context information, is then received/estimated by the controller for remote control. However, scheduling multiple sensors and designing the controller with limited resources is challenging due to their coupling, delay, and transmission loss. We formulate a Constrained Markov Decision Problem (CMDP) to minimize violation probability with cost constraints. We reveal the relationship between the goal and different updating actions by analyzing the significance of information that incorporates goal-related usefulness and contextual importance. Subsequently, a goal-oriented deterministic scheduling policy is proposed. Two sensing-assisted control strategies and a control-aware estimation policy are proposed to improve the violation probability-cost tradeoff, integrated with the scheduling policy to form a goal-oriented co-design framework. Additionally, we explore retransmission in downlink transmission and qualitatively analyze its preference scenario. Simulation results demonstrate that the proposed goal-oriented co-design policy outperforms previous work in simultaneously reducing violation probability and cost.

We propose a transfer learning enhanced hybrid model for robust reference signal received power (RSRP) prediction. The hybrid model comprises an expected RSRP estimation based on transmit power, 3-D antenna gain models, path loss, and a deep learning (DL) for predicting an error from ground-truth measurement. The DL architecture consists of regression neural network (NN) and convolutional neural network (CNN). Besides cell site configuration and the long-term evolution (LTE) measurement report from user equipments (UEs), the expected RSRP and geospatial data e.g. building percentage and clutter index are considered. Since trained model may not perform well in new environment, it requires tedious work and long time to collect data at a new cell site. Therefore, we use transfer learning (TL) to apply the trained model to the other areas, which have differences in environment information and antenna configurations, by transferring the knowledge acquired from trained model. The results of the trained area show that root mean square error (RMSE) and mean absolute error (MAE) are approximately 2.92 and 2.01, respectively. For the other area, TL have improved MAE approximately 1 to 2.

Age of Information (AoI) has been proposed to quantify the freshness of information for emerging real-time applications such as remote monitoring and control in wireless networked control systems (WNCSs). Minimization of the average AoI and its outage probability can ensure timely and stable transmission. Energy efficiency (EE) also plays an important role in WNCSs, as many devices are featured by low cost and limited battery. Multi-connectivity over multiple links enables a decrease in AoI, at the cost of energy. We tackle the unresolved problem of selecting the optimal number of connections that is both AoI-optimal and energy-efficient, while avoiding risky states. To address this issue, the average AoI and peak AoI (PAoI), as well as PAoI violation probability are formulated as functions of the number of connections. Then the EE-PAoI ratio is introduced to allow a tradeoff between AoI and energy, which is maximized by the proposed risk-aware, AoI-optimal and energy-efficient connectivity scheme. To obtain this, we analyze the property of the formulated EE-PAoI ratio and prove the monotonicity of PAoI violation probability. Interestingly, we reveal that the multi-connectivity scheme is not always preferable, and the signal-to-noise ratio (SNR) threshold that determines the selection of the multiconnectivity scheme is derived as a function of the coding rate. Also, the optimal number of connections is obtained and shown to be a decreasing function of the transmit power. Simulation results demonstrate that the proposed scheme enables more than 15 folds of EE-PAoI gain at the low SNR than the single-connectivity scheme.

We consider a wireless networked control system (WNCS) for real-time applications. Different physical processes (e.g., dynamic plant state and Markov Process-based context information) are monitored by multiple sensors via imperfect wireless links and then received/estimated by the controller for remote control. In this paper, we use violation probability as a key performance metric, which captures extreme events that violate the preset threshold of the plant state, to ensure the stability of WNCS. Scheduling multiple sensors with limited resources is challenging, due to the delays and loss in transmission, and their heterogeneous impacts on the WNCS goal. To address this problem, we first show the relationship between the considered goal and the actions of the scheduler and controller. We then present a Markov Decision Problem (MDP) to minimize violation probability with cost constraints. By analyzing the significance of information that incorporates goal-related usefulness and contextual importance, the structural results of the formulated MDP is presented. Then a goal-oriented scheduling and control co-design policy is proposed to improve the violation probability-cost tradeoff. Simulation results show that the proposed policy results in a lower violation probability and a lower cost.

Effective communication service for a Virtual Power Plant (VPP) is a major challenge as a VPP has very stringent latency and reliability requirements for communication with the Distributed Energy Resources (DERs). Network slicing is a promising solution to this challenge as network slices can be customized and provisioned to satisfy the requirements of the VPP's communication traffic. While determining the resources required for the network slice, it is important to consider the location of the VPP server and the paths along which the traffic is routed as significant latency can be experienced if the DERs are spread across a large area. The server's placement and traffic paths chosen can also impact the cost incurred as it would impact the required bandwidth on the links. We formulate a VPP Server Placement and Provisioning Problem that determines i) placement of VPP server, ii) paths for traffic distribution and iii) required bandwidth on each link in a wide area network connecting the DERs and the server while satisfying latency constraints and minimizing cost of reserving bandwidth on the links. We develop a heuristic algorithm for the formulation to obtain an effective solution in reasonable time. We also present a modified, convex version of the formulation under certain constraints through which an optimal solution can be obtained. We demonstrate the performance of our heuristic algorithm by comparing it with the optimal solution for the convex problem and another heuristic approach.

Radio interference or jamming can cause isolated area in advanced metering infrastructure (AMI) based on Wire-less smart utility network (Wi-SUN), in which conventional recovery techniques cannot cope with. In this paper, we deploy narrowband internet-of-things (NB-IoT) interface to some smart meters to act as emergency gateway, called ResiLite. An optimal ResiLite placement algorithm for enhancing network resilience is proposed. We define an implicit resilience metric based on path diversity and cluster closeness. The defined metric is used to form an integer linear programming (ILP) problem, then we solve the ILP to obtain optimal ResiLite placement. Simulation results show that the optimal ResiLite placement improves Wi-SUN AMI network resilience (defined as the number of surviving nodes with packet delivery ratio (PDR) above 99% under disturbance) by up to 167% compared to an AMI without ResiLite, and up to 29% compared to uniformly random ResiLite placement, respectively.

Cyclically shifted partial transmit sequences (CS-PTS) has conventionally been used in SISO systems for PAPR reduction of OFDM signals. Compared to other techniques, CS-PTS attains superior performance. Nevertheless, due to the exhaustive search requirement, it demands excessive computational complexity. In this paper, we adapt CS-PTS to operate in a MIMO framework, where singular value decomposition (SVD) precoding is employed. We also propose SWAN, a novel optimization method based on swarm intelligence to circumvent the exhaustive search. SWAN not only provides a significant reduction in computational complexity, but it also attains a fair balance between optimality and complexity. Through simulations, we show that SWAN achieves near-optimal performance at a much lower complexity than other competing approaches.

Advanced metering infrastructure (AMI) based on Wireless Smart Utility Network (Wi-SUN) employs carrier sense multiple access (CSMA), hence suffers from poor network performance when the number of nodes increases but without proper design of data collection scheduling. In this paper, we introduce an interference-aware TDMA-like optimal data collection scheduling, in which a link-timeslot assignment problem is formed by considering interference constraint to achieve better spatial timeslot reuse. A constraint for achieving consecutive flow for multi-hop transmission is also introduced to avoid modifications on the original CSMA protocol, and hence the proposed scheduling is standard compliant. Our results show that the proposed scheduling reduces the total data collection time of Wi-SUN AMI network with 100(200) smart meters by 59%(48%), 33%(32%), and 19%(13%), respectively, when compared with conventional Wi-SUN AMI, conventional TDMA scheduling and heuristic scheduling based on 2-rank distance interference model.

Blind selected mapping (blind SLM) is an effective peak-to-average power ratio (PAPR) reduction technique which does not require side information sharing. In the blind SLM, the receiver employs phase rotation sequence estimation, which can be carried out using maximum-likelihood (ML) estimation or 2-step sequence estimation using Viterbi algorithm. ML estimation typically requires much higher computational complexity. Recently, we showed that the use of codebook generated from a 2-level phase rotation set {0°, 135°} and the ML phase rotation sequence estimation based on the fourth-power QAM constellation requires much less complexity compared to the conventional blind SLM with 3-level phase rotation set {0°, 120°, 240°} and ML estimation based on original QAM constellation. However, for a large number of phase rotation sequences, the computational complexity still remains high. In this paper, in order to further reduce the computational complexity, we propose a combined use of a 2-level phase rotation set {0°, 135°} and the 2-step sequence estimation. The use of 2-level phase rotation set significantly reduces the number of branches and states in the Viterbi algorithm and hence, leads to complexity reduction. Simulation results confirm that the blind SLM using the 2-level phase rotation set and the 2-step sequence estimation has less computational complexity while achieving similar BER to the ML sequence estimation.

In this paper, the channel estimation (CE) scheme suitable for MIMO cooperative transmission using time division duplex (TDD) in a high mobility environment is considered. We propose a decision-feedback linear prediction (DF-LP) CE scheme, which is used during data transmission. The uncoded bit error rate (BER) performances of OFDM downlink using maximal ratio transmit diversity (MRTD) and single-carrier (SC) uplink using minimum mean square error combining diversity (MMSECD) are evaluated by computer simulation. It is confirmed that the proposed DF-LP CE scheme can significantly improve the BER performance in a very high mobility environment.

Blind selected mapping (blind SLM) is an effective peak-to-average power ratio (PAPR) reduction technique, in which the phase rotation sequence which has been used at the transmitter is blindly estimated. The Euclidean distance between the received symbols after de-mapping and the original QAM constellation is used for the estimation, which requires high computational complexity. In this paper, we introduce a phase rotation sequence estimation based on the minimum Euclidean distance of the fourth-power constellation. The use of fourth-power constellation reduces symbol candidates in minimum Euclidean distance calculation and hence, contributes to complexity reduction. A set of phase rotation sequences constructed by random selection from {0°, 135°} are also introduced to further reduce the complexity and maintain high estimation accuracy. Simulation result confirms that the proposed phase rotation and sequence estimation technique can reduce the complexity without degrading the uncoded bit error rate (BER) performance for the given PAPR reduction.

Multi-User Multiple Input Multiple Output (MU-MIMO) can significantly increase the link capacity without bandwidth expansion. One promising technique is MMSE-SVD, which is a combination of minimum mean square error (MMSE) filter at the base station (BS) side and eigenmode filter generated by singular value decomposition (SVD) at user equipment (UE) side. MMSE-SVD requires BS and UEs to share the MIMO channel state information (CSI) prior to data transmission. This may cause a serious problem in a high mobility environment; the shared MIMO CSI becomes outdated and consequently, the bit-error rate (BER) performance degrades. In this paper, we propose an adaptive MMSE-SVD, which updates the transmit filter using channel prediction and the receive filter using decision-feedback channel estimation. The uncoded BER performance of adaptive MMSE-SVD for orthogonal frequency division multiplexing (OFDM) downlink and single-carrier (SC) uplink is evaluated by computer simulation. Simulation results confirmed that adaptive MMSE-SVD increases the allowable maximum Doppler frequency ( fDT) for keeping by about 4 times for OFDM downlink while by about 1.6 times for SC uplink.

We have been studying cooperative distributed antenna transmission (CDAT) as a promising technique for realizing the 5thgeneration (5G) high-speed mobile communications. Assuming time division duplex (TDD), the macro-cell base station (MBS) and the user equipments (UEs) conduct the channel estimation independently to obtain the shared channel state information (CSI). In this paper, we introduce a TDD frame structure consisting of uplink pilot time slot and downlink pilot time slot followed by data time slots. MIMO channel estimation is done before the user data transmission. Also presented is the pilot signal design. The accuracy of the proposed MIMO channel estimation and achievable bit error rate (BER) performance of user data transmission are evaluated by computer simulation.

Blind selected mapping (blind SLM) can effectively reduce the peak-to-average power ratio (PAPR) of both orthogonal frequency division multiplexing (OFDM) and single-carrier (SC) signals without side-information transmission. In typical blind SLM, maximum likelihood (ML) estimation is applied to find the de-mapping phase rotation sequence which gives the lowest Euclidean distance among all possible sequences, resulting in very high computational complexity. In this paper, we introduce a novel low-complexity 2-step estimation suitable for blind SLM. In the first step, the phase rotation sequence achieving the lowest Euclidean distance is searched by using the Viterbi algorithm. In the second step, verification and correction are carried out to choose a phase rotation sequence stored in the codebook, which has the lowest Hamming distance from the estimated sequence in the first step. It is confirmed by computer simulation that our proposed 2-step estimation achieves similar BER performance to the transmission without SLM and the transmission with blind SLM with the conventional ML estimation, but the proposed estimation technique requires much less complexity.

Distributed antenna small-cell network is a promising 5G network. In this paper, a comprehensive report of recent advance in the cooperative distributed antenna transmission (CDAT) is provided. Single-user space-time block coded transmit diversity (STBC-TD) and multi-user minimum mean square error filtering combined with singular value decomposition (MMSE-SVD) are presented. Also presented is blind selected mapping (blind SLM) which can suppress the peak-to-average signal power ratio (PAPR) and requires no side information transmission. The effectiveness of CDAT in the presence of co-channel interference (CCI) from adjacent macro- cells is confirmed by computer simulation.

Single-carrier (SC) signal has a low peak-to-average power ratio (PAPR) property. However, the PAPR of SC signal increases if transmit filtering and/or high-level modulation are applied. We have recently proposed a time-domain selected mapping (TD-SLM) which effectively reduces the PAPR of filtered SC signals by applying the binary phase rotation before transmit filtering, but the necessity of side-information decreases the spectrum efficiency (SE). In this paper, a blind TD-SLM which does not require side-information is proposed. Unlike the frequency-domain SLM (FD-SLM) and the original TD-SLM with side-information, polyphase rotations are used. Performance evaluation of the proposed blind TD-SLM is done by computer simulation assuming turbo-coded filtered SC block signal transmission in aspects of PAPR and bit-error rate (BER) to show that no significant BER performance degradation is occurred.

Abstract Single‐carrier transmission with frequency‐domain equalization (SC‐FDE) is widely known as a promising transmission technique providing low error probability with low peak‐to‐average power ratio (PAPR) of transmit signal. However, the low‐PAPR property of SC‐FDE cannot be maintained if multi‐level data modulation is introduced. The low‐PAPR property of SC‐FDE can be maintained by applying transmit filtering with roll‐off factor at the expense of spectrum efficiency. In this paper, we propose two types of selected mapping (SLM) to reduce the PAPR of SC‐FDE transmit signal. The first SLM technique is conducted in the frequency domain, where the phase rotation is applied to subcarriers similar to the SLM technique for orthogonal frequency division multiplexing transmission. The second SLM technique is conducted in the time domain, where the phase rotation is applied directly to data‐modulated symbol sequence. Computer simulation confirms that both SLM techniques are able to reduce the PAPR of SC‐FDE signal without significant degradation of bit‐error rate performance and spectrum efficiency. Copyright © 2016 John Wiley & Sons, Ltd.

In this paper, a novel spectrum efficient single-sideband single-carrier (SC) with frequency-domain equalization (SSB-FDE) using amplitude shift keying (ASK) modulation (ASK SSB-FDE) is proposed. Similar to the conventional SC transmission with FDE (SC-FDE), the ASK modulated symbol block to be transmitted is transformed by discrete Fourier transform (DFT) into frequency-domain signal. Then, inverse DFT (IDFT) is applied to the upper (or lower) sideband spectrum to obtain the time-domain SSB signal block. The cyclic prefix (CP) inserted SSB signal block is transmitted over a frequency-selective fading channel. At a receiver, the minimum mean square error (MMSE) based FDE is applied. ASK SSB-FDE has lower peak-to-average power ratio (PAPR) and better throughput performance than QAM SC-FDE when the throughput is plotted as a function of peak transmit SNR. This is confirmed by computer simulation assuming a frequency-selective Rayleigh fading channel.

Joint transmit/receive frequency-domain equalization based on minimum mean-square error criterion (joint Tx/Rx MMSE-FDE) is a promising frequency-domain-based technique suppressing inter-symbol interference (ISI) in broadband single-carrier (SC) transmission. However, it changes the frequency-domain spectrum shape and hence increases the peak-to-average power ratio (PAPR) of transmit signal. In this paper, we introduce the selective mapping (SLM), which is typically used in orthogonal frequency division multiplexing (OFDM), to reduce PAPR of SC transmission using joint Tx/Rx MMSE-FDE. The SLM is applied to the frequency-domain SC signal after applying the transmit FDE (Tx-FDE) and prior to inverse fast Fourier transform (IFFT). It is shown, by computer simulation, that the SLM can reduce PAPR without significant effect on bit-error rate (BER). Performance of SLM is also evaluated in various phase-rotation sequence types, in both deterministic and random points of views, and number of candidates. Computational complexity of the proposed transmission scheme employing SLM algorithm is also discussed.

Single-carrier transmission is a promising transmission technique due to its low peak-to-average power ratio (PAPR) property compared to multicarrier transmission, and using frequency-domain equalization (FDE) at the receiving side also mitigate the adverse effect of channel frequency-selectivity. An introduction of transmit filter can improve the system performance in terms of either PAPR or error probability. In this paper, we focus on the transmit filter aiming to reduce PAPR by employing the minimization of variance of instantaneous transmit power. Filter roll-off factor is also considered in order to provide excess-bandwidth transmission. With a combination of an FDE and spectrum combining at the receiver, excess-bandwidth transmission inherits additional frequency diversity gain, and therefore improves error probability. Performance evaluation of the proposed filtering algorithm is done by computer simulation, while the PAPR and bit-error rate (BER) performance of proposed algorithm are compared with conventional square-root Nyquist filter.