This paper investigates the scenario where unmanned aerial vehicle (UAV) relay systems transmit ultra-reliable and low-latency communication (URLLC) command packets among devices under the interference from fixed-position sources. Constrained by finite blocklength, we optimize the blocklength allocation and location of UAV to minimize the decoding error rate. To optimize this sparse reward problem, an iterative optimization approach is introduced based on the Twin Delayed DDPG (TD3) deep reinforcement learning (DRL) algorithm. The simulation experiments indicate that the proposed iterative algorithm significantly outperforms the TD3, DDPG, and PPO algorithms when used individually, while also approaching the performance of the exhaustive algorithm. This research provides an effective solution to enhance the communication performance of UAV relay systems for short packet transmission in the presence of interference.

Facing the new era of the innovations and integration between virtual reality (VR) and the Internet of Things (IoT), the characteristics and model of VR traffic need to be studied to provide better quality of service guarantee. In this work, we simulate a testbed where the wearable VR glasses is connected into the wireless network provided by the server. And the VR traffic is studied from the two aspects of deterministic and stochastic component respectively. At the same time, the arrival curve in network calculus is used to build the traffic model and a novel method for VR traffic modeling is proposed. The theoretical curves in our proposed model are compared with existing theoretical methods and measured statistical data to verify the feasibility of our proposed model. Simulations indicate that our proposed method outperforms the existing method.

With the growing popularity of wearable devices, body-centric networks have become the focus of Internet of Things (IoT) research. However, malicious eavesdroppers and attackers pose threats to user privacy and network secrecy. Fortunately, physical layer security (PLS) communication and covert communication (CC) have been introduced and can be used in body-centric networks. However, network performance of both secrecy techniques has not been analyzed with an accurate wireless fading model. To fill this research gap, we study a body-centric IoT communication system with information secrecy features based on PLS and CC techniques. By adopting the Alternate Rician Shadowed fading model, we derive closed-form expressions for the secrecy outage probability and secrecy rate in PLS, and the detection error probability and covert rate in CC. To provide more explicit guidance, an algorithm for the selection of PLS and CC techniques is proposed, which aims to reach a high transmission performance state while ensuring communication security and covertness. The secrecy rate and covert rate are analytically and empirically compared. We insightfully find that, with the help of a friendly jammer, CC performs better than PLS, especially with high transmit power. However, an upper boundary of transmit power exists to ensure communication covertness in CC.

Satellite communication has become a hot topic in the development of the sixth-generation (6G) mobile communication due to its advantage of wide coverage and broadband transmission. Dual polarization frequency reuse (DPFR) is often used to improve the spectrum utilization in satellite communication system. However, cross-polarization interference (XPI) often occurs owing to the imperfect devices and atmosphere conditions. This paper proposes a joint convolutional neural network (CNN) and long short-term memory (LSTM) network to cancel the XPI for satellite communication. Since the cross-polarization interference cancellation (XPIC) is normally implemented at baseband, it is inevitable that nonlinear effects will be introduced by the high-power amplifier (HPA) on satellite. Conventional XPIC schemes based on transversal filter can not deal with the nonlinear impairments of the received signal, resulting in poor bit error ratio (BER) performance. We combine CNN and LSTM to extract the nonlinear feature and temporal correlation of the received signal, which can effectively eliminate the XPI and nonlinear effects. Simulation results show that, compared with conventional XPIC schemes, the BER performance of proposed scheme is improved by two orders of magnitude when the signal-to-noise ratio (SNR) is 20 dB. Besides, the proposed scheme can achieve fast convergence with small mean square error (MSE).

Driven by growing concern about environment, a major issue with the 5G is the energy consumption of user equipment. Discontinuous reception (DRX) is a key technique to cope with it. DRX mechanism was firstly introduced into standard in L TE and relative enhancements have been put forward and discussed widely in recent 3GPP standardization process. Introducing wake up signal (WUS) is one of them. This promotion can greatly reduce the energy consumed by UE, while bringing extra signal overhead. In this paper, an enhanced WUS scheme is proposed to improve the performance of signal overhead without much compromise on other indicators. Various sets of parameters are used to test its impact on the performance. Results are obtained with system level simulation which is validated with the data in 3GPP specification. Results prove that the enhanced scheme can get a better overall performance. Using this scheme, DRX can quickly adapt to different traffic without changing the basic DRX parameters.

In this paper, the buffer-constrained throughput performance of a multi-user wireless-powered communication (WPC) system is investigated, where energy harvesting follows a non-linear model. The investigation focuses on the buffer overflow performance of sending data in the downlink (DL) from the access point (AP) node to each user equipment (UE) node and that in the uplink from each UE node to the AP node, based on which the throughput performance on both directions when a buffer constraint is enforced is studied. Specifically, the buffer overflow probability at each node is analyzed, based on which the buffer-constrained throughput is studied. In addition, to ensure the throughput performance under the buffer constraint, the DL transmission power allocation policy and the required energy storage capacity at each UE are investigated. Also, the optimal channel time allocation policy is studied with the objective of maximizing the minimum buffer-constrained throughput guaranteed to each UE at the same time. To this aim, an optimization problem is first formulated and then a dichotomy-based time allocation algorithm combined with a one-dimensional search is proposed to solve this problem. The analysis and results, explicitly relating the throughput to the buffer constraint in addition to WPC characteristics, shed new light on the design and performance analysis of WPC systems.

As one of the crucial application scenarios, URLLC (Ultra-Reliable and Low Latency Communication) has been put on the agenda with the development of the 5G communication technology. This paper focuses on the downlink evaluation of shortened TTI (Transmission Time Interval), which is the pivotal characteristic of URLLC. In order to describe the varying control overhead of shortened TTI, we propose a model basing on the traffic arriving rate and the TTI length. What's more, we design a downlink scheduling algorithm to take the impact of shortened TTI into consideration. The system-level simulation verifies that shortened TTI is able to achieve high throughput as well as low latency due to low transmission delay at low system load. However, benefit brought by shortened TTI decreases as the load increases since its higher relative control overhead may lead to non-negligible queuing delay facing high system load. In this situation, system should choose relatively long shortened TTI configurations to reduce the influence of queueing delay.

In this paper, we investigate the delay and delay-constrained throughput performance of a point-to-point wireless-powered communication system, where one node, e.g. a user equipment (UE), is powered by the wireless energy transferred from the other node, e.g. an access point (AP), and uses the harvested wireless energy to send data to the other node. Our focus is on the delay performance of sending data over the uplink from the UE node to the AP node, and on its throughput performance when a delay constraint is enforced. Two representative time allocation schemes in using the link for the AP node to transfer energy (maybe together with data) and for the UE node to send data are considered. In particular, a lower bound on the cumulative capacity of the uplink is derived. In addition, an upper bound on the delay distribution is obtained for stochastic traffic arrivals, based on which, the delay-constrained throughput performance is further analyzed. Moreover, the accuracy of the analysis is validated by comparison with extensive simulation results. The analysis and results shed new light on the performance of such a wireless-powered communication system.

In this paper, a spectrum sharing scheme adapted for the operation of Long Term Evolution (LTE) in unlicensed band (LTE-U) and WiFi system is proposed. This scheme optimizes the resource in unlicensed band based on decision tree learning and repeated game. We consider a flexible architecture decoupling control plane from data plane in the coexistence system. In control plane, strong ability of data processing is provided. Controllers learn the latest data set in the pool to build decision trees. According to the decision tree, controllers deduce the network status of the opponent. Repeated game is played to share spectrum resources for maximizing the resource utilization in the coexistence system. At the beginning of each game stage, controllers use decision tree to make informed decisions quickly. In repeated game, an encouragement mechanism is proposed to stimulate operators to share spectrum resources. Simulation results show that dynamic spectrum sharing is able to improve throughput and spectrum efficiency in unlicensed band. At the same time, this scheme also balances the traffic load and guarantees fairness among multiple systems.

Studies of multi-server networks are usually conducted on the assumptions of independent servers and specific arrivals, which may not capture the characteristics of realistic networks. In this paper, we propose a novel stochastic network calculus approach to perform delay analysis for a general multi-server network. The stochastic network service curves are derived in two ways with different assumptions. After that, we use these service curves to derive queueing delay bounds including delay bound distribution and mean delay bound for a specific scenario of which the classical M/M/N model is a subset. Compared with previous studies, it is worth highlighting that our analysis contains the cases where the arrival and service processes as well as the servers can either be independent or correlated. In addition, the accuracy of the analytical delay bounds are verified by comparing with the queueing theory results in an M/M/N model.

Energy evaluation of wireless transmission for data service under different QoS (quality of service) constraints is a hot topic in green communications. In this paper, we employ the theory of the stochastic network calculus to investigate the relationship between the traffic arrival rate and energy harvesting rate under the delay and energy storage constraints. We first construct a wireless system model which works only by consuming the harvested renewable energy. Also, stochastic traffic arrivals, packet size as well as a two-state Markov chain interference on energy harvesting are jointly considered to ensure the accuracy of the analysis. We derive the minimum energy harvesting rate needed to satisfy the delay and energy storage constraints under a given average arrival rate. The efficiency of the harvested energy is also studied and shown to be convex in the numerical simulation. Numerical results illustrate that while the minimum energy harvesting rate is positively correlated with the packet size, it is negatively related to the delay requirement, under a given arrival rate. Additionally, the probabilistic bound of energy insufficiency is shown to be positively correlated with the transition cycle of the interference.

Ultra-dense Small Cell deployment is a sensible design of heterogeneous network, which provides a good performance of hot spots coverage enhancement and traffic load balancing. The growing energy consumption pressure becomes one of the main challenges of the Small Cell application. Cloud Radio Access Network (C-RAN) can promise significant energy consumption savings for Small Cells via the separation between RRH and BBU. In this paper, we propose a novel software defined C-RAN (SDC-RAN) architecture in Small Cell network. Moreover, a self-adaptive power adjustment scheme (SA-PAS) is introduced, considering the influence of users' current and history traffic demands during downlink power allocation. The goals are to strike a good balance between energy efficiency and user experience. Simulation results show that the expected system throughput can be achieved with limited resource consumption in SDC-RAN based on Small Cell deployment.

A sensible design of ultra-dense Small Cell network involves striking a good balance between energy efficiency and user experience especially in hot spots. In this paper, we propose a self-organized resource allocation scheme (SO-RAS) as an enhanced solution for the system performance, which can coordinate resource allocation within Small Cell clusters based on the self-organized mechanism. We take the users' access distribution as a constraint weight when conducting downlink cooperative power adjustment, aiming to adapt system resource consumption corresponding with the current traffic load. Simulation results show that the proposed strategy improves system performance in hot-spot users' throughput and can contribute to the system energy efficiency ratio in ultra-dense networks.

The dynamic uplink-downlink reconfiguration of TD- LTE is regarded as an effective method to increase the resource efficiency and optimize the system performance. With different transmission directions and the dense deployment of small cells in the heterogeneous network, the interference situation becomes complex and critical in both uplink and downlink, especially for the cell-edge UE. In this paper, we discuss the interference coordination and mitigation problem in the dynamic TDD network. With cell-clustering interference mitigation, the synchronous operation can be provided in a cluster and well isolation can be obtained between cells in the different clusters. Furthermore, we propose that the simplified downlink CoMP DCS mode can be used in the clusters to optimize the downlink performance. At last of the paper, we analyze the performance gain of the proposed scheme by system level simulation. The results show that both uplink and downlink performance for the cell-edge UE are improved.

Relay-assisted Device-to-Device (D2D) communication is an enhanced technology for D2D communication. With relay nodes' assistances, the communication distance of the D2D pair is extended and the quality of communication can be improved. This paper focuses on the achievable transmission capacity of relay-assisted D2D network while keeping a low outage probability of the cellular users. based on stochastic geometry, the mathematical model of relay-assisted D2D network, with relay selection criterion, is formed and analyzed. Subsequently, the optimal transmission power ratio of the cellular system to the D2D system and the optimal relay selection range are derived. Furthermore, the achievable transmission capacity with derived optimal parameters is presented as a close-form expression. Then the numerical results show that the performance of the D2D network can be improved by relay-assisted transmission in case of poor wireless environment. In addition, the influences of the densities of both cellular, D2D and relay users and the communication distances between D2D pairs are evaluated in this paper.

The green communication draws a lot of attention in recent years. Meanwhile, as a promising technology, cognitive radio will constitute an important part of the future communication networks. Energy consumption of cognitive radio network is worthy studying, which is analyzed in this paper applying stochastic network calculus. A multi-channel cognitive radio network model is introduced. Stochastic network calculus is then used in the analysis, which is a newly developed theory dealing with queuing system found in computer networks. Guaranteed service for secondary users is firstly derived, followed by stochastic service curve derivation. Then, minimum transmission rate is conducted which is an important variable in energy analysis. After that, relationship between energy consumption and transmission rate is presented. As part of the derivation, delay bound and transmission power are discussed. Finally, numerical results of transmission rate, transmission power and energy consumption are shown for different constraint, where the influence of channel quantity is further discussed.

Dynamic uplink and downlink reconfiguration is studied as an effective method to improve the system packet throughput performance in the LTE Heterogeneous Network. There are various kinds of traffic with different quality of service requirements in the practical wireless network, which has not been fully considered by the existing resource allocation strategies for dynamic TDD. In this paper, a resource allocation scheme coordinating the time and frequency resource for mixed traffic in the dynamic TDD scenario is proposed, which can guarantee the system requirements, such as time delay budget, packet drop rate and packet throughput. Utilities of users with different services are considered in the scheduling and dynamic UL-DL reconfiguration. Theoretical analysis and system level simulation are carried out to evaluate the performance. The simulation results show that compared with the existing resource allocation schemes, the proposed one offers a better performance, which are low packet drop rate of VoIP users and high packet throughput of FTP users.

In this paper, we propose an effective resource allocation scheme in macrocell/femtocell OFDMA uplink networks. A cross-layer mitigation algorithm is designed firstly to avoid the severe cross-layer interference which will decouple the resource allocation between two networks. Then utilizing the result of cross-layer mitigation, a resource allocation strategy including power allocation and frequency assignment is proposed to meet the UE's target data rate and obtain better throughput performance. Simulation results show that the proposed algorithm can achieve significant performance gains over the traditional methods, especially in view of the guarantee of UE's quality of service (QoS) and throughput performance.

Weighted Cooperative Spectrum Sensing (WCSS), an important technique in Cognitive Radio (CR), requires all the Secondary Users (SU) to send their sensing data to the Fusion Center (FC) periodically, ignoring the fact that the difference between two consecutive sensing data of the same SU could be small. In order to reduce the overhead transmission in the WCSS, this paper seeks an effective scheme from two aspects. First, a quantization method is introduced to help reduce overhead transmission. To further reduce the amount of overhead, a differential scheme in which each SU sends only the difference between its two consecutive sensing data is proposed. The whole work is conducted under the Variable Length Quantification (VLQ) transmission scheme.

CDMA2000, WCDMA and WiMAX are three widely used 3G technologies. Since they share the same goal, which is to provide broader coverage and higher throughput in 3G networks, an impartial comparison of their performance is indispensable. However, they are based on different design principles and methodologies, which make the comparison challenging. This paper presents a comparative study of these technologies, with focus on system spectral efficiency and stability in 3G networks. Specifically, the paper presents a framework for the comparison based on the common set of configurations adopted by these technologies, which include channel models, system parameters and key algorithms. Through extensive simulations, the system spectral efficiency and stability of CDMA2000 1x EV-DO Rev.A, WCDMA HSDPA/HSUPA and mobile WiMAX are compared. It is found that while WiMAX can provide highest throughput, the two CDMA-based technologies achieve higher system spectral efficiency, especially on the downlink. Regarding system stability, it is observed that CDMA2000 1x EV-DO Rev.A can operate under higher interference levels than WCDMA HSDPA/HSUPA and mobile WiMAX. In addition, the comparison on system spectral efficiency between CDMA2000, WCDMA and WiMAX is also conducted when relevant enhanced technologies, i.e., MIMO and interference cancellation, are adopted. We believe that our work will serve as a cornerstone for a fair comparison between the various technologies for prospective 3G networks.

In this paper, we investigate the potential benefit of successive interference cancellation (SIC) in high speed uplink packet access (HSUPA). We explore the possibility of improving the performance of HSUPA by introducing the SIC and we also bring forward a novel scheduling method named effective power-based load control (EPBLC) to extend its advantage. Finally we give the conclusion that with SIC and EPBLC, we can get 43%-56% throughput gain under different interference cancellation efficiency.

Mobile WiMAX has become one of the 3 Generation communication systems and its performance has been widely evaluated. The physical overhead is a critical factor that may affect the overall performance significantly. But almost no attention has been paid to the impact of overhead on system performance yet. In this paper, we first analyze main signaling resources needed in physical layer, which consist of the physical overhead. Then the dynamic overhead model for downlink and uplink are proposed respectively and simplified, while maintaining the simulation accuracy. Average overhead amount is obtained through system level simulation using dynamic overhead calculation. Finally, it is proved that the model is reasonable and the average overhead size may be used in stead of dynamic calculation for the sake of reducing simulation complexity as well as keeping evaluation results precise.

On the reverse link of CDMA systems, two options are possible for resource allocation: rate control (RC) and centralized scheduling (CS). The rate control algorithm can be further divided into Common Rate Control (CRC) and Dedicated Rate Control (DRC). In CRC, each mobile station (MS) independently determines its reverse link rate using the system interference level information broadcasted by a base station (BSs) and rate control mechanism at the MS side. While in DRC, the BS sends each MS a rate movement command. On the other hand, centralized scheduling directly assigns reverse link rates to a subset of MSs. In this paper, the Token Bucket based Common Rate Control (TB- CRC) mechanism is discussed and compared with the centralize scheduling. Performances have been evaluated through system level simulation. It is shown that the token bucket based rate control philosophy outperforms the centralized scheduling from the aspect of throughput, fairness, system stability, signaling overhead and transmission delay.

This paper proposes a novel power control algorithm on the reverse link (RL) of the CDMA system, which takes the interference interaction among mobile stations (MSs) into consideration. The proposed algorithm is based on power control commands with the assumption that each MS can collect power control information for other MSs in the same cell as references to determine its own transmit power. The action of keeping current transmit power is introduced to MS. So the power variation is smaller and the system is more stable compared with the traditional power control algorithm. It is shown, by dynamic system level simulation, that the proposed algorithm can reduce interference and improve system capacity. In addition, the proposed algorithm is flexible to implement, since it can be located at MS or base station.