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To exploit richer spectrum resources for even better service quality, millimeter wave (mmWave) communication has been considered for high-speed railway (HSR) communication systems. In this paper, we focus on scheduling as many flows as possible while satisfying their QoS requirements. Due to interference, eavesdropping, or other problems, some flows may not be directly transmitted from the track-side BS. In this paper, we propose an UAV-assisted scheduling scheme which utilizes a UAV to serve as relay for such flows. The proposed scheme also utilize two mmWave bands, one for the BS links and the other for the UAV links. The proposed algorithm aims to maximize the number of flows with their QoS requirements satisfied. Simulations demonstrate that the proposed scheme achieves a superior performance on the number of completed flows and the system throughput over two baseline schemes. [ABSTRACT FROM AUTHOR]

In this paper, we study the average throughput performance of energy beamforming in a multi-antenna wireless-powered communication network (WPCN). The considered network consists of one hybrid access point (AP) with multiple antennas and a single-antenna user. The user has no constant power supply and, thus, needs to harvest energy from the signals broadcast by the AP in the downlink (DL) before sending its data back to the AP with the harvested energy in the uplink (UL). We derive closed-form expressions of the average throughput and their asymptotic expressions at a high SNR for both delay-limited and delay-tolerant transmission modes. The optimal DL energy harvesting time, which maximizes the system throughput, is then obtained for high SNR. All analytical expressions are validated by numerical simulations. The impact of various parameters, such as the AP transmit power, the energy harvesting time, and the number of antennas, on the system throughput is also investigated. [ABSTRACT FROM AUTHOR]

In nonsaturated 802.11 distributed coordination function (DCF) networks, existing studies had observed a salient phenomenon: the maximum stable throughput may be far higher than the saturation throughput and last for a long duration (say, months). Such a maximum stable throughput is called the presaturation throughput peak. The long-duration peak suggests that 802.11 DCF networks may provide a far higher stable throughput than what we generally believe, without worrying about a sudden deterioration of quality of service (QoS). This paper is devoted to developing a general theoretical framework to predict the peak. In the framework, we define a backoff entropy to quantify the uncertainty of the inherent random backoff process of 802.11 DCF networks, and then innovatively introduce a BackoffEntropy-Peak linearity property (i.e., the peak is linearly proportional to the backoff entropy) for the peak prediction. This framework is applicable for a general configuration of contention windows (CWs). It enables us to reveal the most essential dependency of the peak on the initial CW size and the number of network nodes. Further, we design peak-based call admission control (CAC) schemes that can be performed quickly and easily, without requiring network performance measurements and complex calculations. We verify our framework and CAC schemes via widely adopted 802.11 DCF ns2 and ns3 simulators (mostly with typical 802.11 standard settings). Extensive simulations show that our framework and CAC schemes trade within 9% peak prediction errors for making 802.11 DCF networks provide high stable throughput with good QoS (such as short delay and low collision probability). This paper is the first to propose applying the information entropy to study the throughput-stability problem. We believe that this study makes a crucial breakthrough in thoroughly investigating nonsaturated performance and network stability of random access wireless networks. [ABSTRACT FROM AUTHOR]

Rail transportation, especially, high-speed rails (HSR), is an important infrastructure for the development of national economy and the promotion of passenger experience. Due to the large bandwidth, millimeter wave (mmWave) communication is regarded as a promising technology to meet the demand of high data rates. However, since mmWave communication has the characteristic of high attenuation, mobile relay (MR) is considered in this paper. Also, full-duplex (FD) communications have been proposed to improve the spectral efficiency. However, because of the high speed, as well as the problem of penetration loss, passengers on the train have a poor quality of service. Consequently, an effective user association scheme for HSR in mmWave band is necessary. In this paper, we investigate the user association optimization problem in mmWave mobile relay systems where the MRs operate in the FD mode. To maximize the system capacity, we propose a cooperative user association approach based on coalition formation game, and develop a coalition formation algorithm to solve the challenging NP-hard problem. We also prove the convergence and Nash-stable property of the proposed algorithm. Extensive simulations are done to show the system performance of the proposed scheme under various network settings. It is demonstrated that the proposed distributed low complexity scheme achieves a near-optimal performance and outperforms two baseline schemes in terms of average system throughput. [ABSTRACT FROM AUTHOR]

As one of the three main application scenarios of 5 G cellular system, massive Machine-Type Communications (mMTC) has been regarded as the key solution to facilitate the IoT paradigm. One major bottleneck for accommodating mMTC is the severe congestion at the cellular random access channel when plenty of Machine-Type Devices (MTDs) send access requests concurrently while the preamble resources are limited. To remedy this issue, limiting the number of retransmissions and dropping access requests after the limit is reached can be an effective approach. Yet, the effect of the preamble retransmission limit $K$ on the optimal access performance of mMTC in cellular networks remains largely unexploited, which motivates the study in this paper. Specifically, in this paper, we start by characterizing the network steady-state points based on the limiting probability of successful transmission of access requests. We then obtain explicit expressions of the access throughput and the mean access delay of successfully-transmitted access requests as functions of $K$ and the number of preambles $M$. The maximum access throughput and the corresponding optimal backoff window size are further derived. It is shown that the maximum access throughput is independent of $K$ , while the mean access delay can be significantly reduced with a small $K$ , yet, at the expense of increased request dropping ratio. In addition, to improve both the throughput and delay performance, the analysis shows that more preambles should be allocated but the performance gain becomes marginal when $M$ is large. Therewith, an algorithm is proposed for determining the least number of preambles $M^\ast$ that maximizes the access throughput and the preamble resource utilization ratio. Numerical results show that a smaller preamble retransmission limit $K$ can further reduce $M^\ast$. [ABSTRACT FROM AUTHOR]

With the explosive growth of mobile data, the demand of high-speed railway (HSR) passengers for broadband wireless access services urgently needs the support of ultra-high-speed scenario broadband wireless communication. Millimeter-wave (mmWave) can achieve high data transmission rates, but it is accompanied by high propagation loss and vulnerability to blockage. To address this issue, developments of directional antennas and unmanned aerial vehicles (UAVs) enhance the robustness of the mmWave train-ground communication system. In this paper, we propose a UAV and MRs relay assistance (UMRA) algorithm to effectively overcome link blockage, which can maximize the number of transmission flows on the premise of meeting QoS requirements and channel qualities. First, we formulate a mixed integer nonlinear programming (MINLP) problem for UAV trajectory design and transmission scheduling in the full-duplex (FD) mode. Then, in UMRA, the relay decision algorithm and transmission scheduling algorithm based on graph theory are proposed, which make a good tradeoff between computation complexity and system performance. Extensive simulation results show that a suitable UAV position will greatly improve the performance of the UMRA algorithm and make it close to the optimal solution. Compared with the other two existing benchmark schemes, with the high channel quality requirements and large-area blockage, UMRA can greatly improve the number of completed flows and system throughput. [ABSTRACT FROM AUTHOR]

As an aerial base station, unmanned aerial vehicle (UAV) has been considered as a promising technology to assist future wireless communications due to its flexible, swift and low cost features, where resource allocation is the basis for ensuring energy-efficient UAV-assisted networks. This paper formulates a joint optimization problem of user association, UAV trajectory design and power control to maximize the channel capacity among all ground users at a limited power level in a downlink transmission. To tackle the mixed-integer non-linear programming problem, this paper proposes a clustering-aided reinforcement learning approach consisting of three consecutive stages. Firstly, modified expectation-maximization unsupervised learning algorithm is investigated to cluster the ground users, which reduces the dimensions and hence, the association complexity is reduced as well. Then, Kuhn-Munkres algorithm is incorporated for user association, which associates a UAV with the ground users via matching to the cluster, and assigns the UAVs to the centroid of the matching cluster for pre-placement, with the aim of speeding up the convergence of the following deep reinforcement learning algorithm. Finally, a multi-agent twin delayed deep deterministic (MATD3) policy gradient is proposed to solve the non-convex sub-problem, which determines the transmit power and designs the fine-tuned trajectory of UAVs. By incorporating low-bias value estimation technique, the reward of the proposed MATD3 algorithm is improved. Simulation results have demonstrated that our proposed approach achieves higher reward as well as converging faster than existing reinforcement algorithms. Besides, the clustering-aided reinforcement learning has lower computational complexity than the benchmark schemes. [ABSTRACT FROM AUTHOR]

Carrier sense multiple access with collision notification (CSMA/CN) is a typical representation of physical-layer (PHY)/medium access control (MAC) co-designs, where the MAC control frames are implemented or detected using PHY techniques. With CSMA/CN, the sender detects an unsuccessful transmission, with the aid of a collision notification (CN) from the receiver. In this paper, we first theoretically study the crucial impact of the CN attributes (namely, the detection threshold and the length) on system throughput in a wireless local area network (WLAN). We identify that the false-alarm probability of CN (more generally, the control frames in PHY/MAC co-designs) is a dominating metric that influences system performance. This paper will help developers select optimal CN attributes to balance various factors influencing CN detection performance. Extensive simulation results verify that our performance model is very accurate. [ABSTRACT FROM PUBLISHER]

The performance of throughput, delay, and their tradeoff in mobile ad hoc networks (MANETs) has been investigated on different assumptions. Nevertheless, few papers consider the supportive infrastructure in MANETs. With the help of supportive infrastructure, i.e., cellular networks, the performance of throughput and delay in MANETs can be improved. The impact of supportive infrastructure on the throughput–delay tradeoff in MANETs is an open research point. In this paper, we are interested in the optimal throughput–delay tradeoff in MANETs with supportive infrastructure. We investigate the supportive infrastructure that only provides transmission pipes between distant nodes. We study the optimal throughput–delay tradeoff in MANETs on different assumptions such as different densities of nodes and base stations (BSs), discrete/continuous mobility models with various velocities, and the fast/slow mobility assumption. We obtain the asymptotically optimal throughput–delay tradeoff and propose transmission policies based on random linear coding (RLC) to achieve the optimal throughput–delay tradeoff asymptotically. From the obtained optimal throughput–delay tradeoff, we find that supportive infrastructure reduces the delay bound from velocity, which is a lower bound of delay caused by nodes' velocity. In particular, if supportive infrastructure can cover the entire network, then the delay bound from velocity vanishes when per-node throughput does not exceed a threshold. Moreover, we find that there also exists a delay bound from the transmission range of the instant transmission. In addition, we observe that, for the optimal throughput–delay tradeoff in the large throughput region, the case in the continuous mobility model outperforms the case in the discrete mobility model, and the case on the slow mobility assumption outperforms the case on the fast mobility assumption. [ABSTRACT FROM PUBLISHER]

Two-path relay networks can be deployed to achieve full-rate transmissions. In this paper, we introduce stable throughput analysis into decode-and-forward (DF) two-path relay networks. We establish the queueing model and take outage probabilities into consideration to characterize the packet-level cooperation and derive the closed-form stable throughput region. Based on the stable throughput region, we also propose a power-allocation scheme between the source node and relays to maximize the achievable packet rate. The maximal achievable packet rate determines the admission control of certain cooperation (i.e., when to cooperate) under a specific interrelay interference (IRI) cancellation technique. The power allocation is utilized to illustrate how to cooperate between the source node and relays. Three IRI responses are considered, and the system behaviors under various circumstances are presented through simulations. [ABSTRACT FROM AUTHOR]

Horizontal antenna sectorization has been used within all generations of cellular radio networks to improve both the coverage and capacity of such networks. This paper evaluates the potential coverage and capacity gains of sectorization through extensive simulation and real-world trials of deployments of higher order horizontal sectorization (three, six, nine, 12, and 15 sectors) when applied to a Third-Generation (3G) Evolved High-Speed Packet Access (\mbox3\mboxG/\mboxHSPA+) network. Simulation results are presented for idealized homogeneous networks based upon a standardized 3G Partnership Project HSPA/Long-Term Evolution (LTE) network model to find the theoretical downlink capacity gains and the optimum horizontal antenna beamwidth to maximize capacity without significantly reducing coverage and other cellular-network key performance indicators (KPIs). Further simulations have also been performed to assess the potential gain seen within Telefonica UK's central London \mbox3\mboxG/\mboxHSPA+ network, and these results have also been verified using live network field results from the deployment of six-sector sites into Telefonica UK's network. Finally, trial results from the deployment of what is believed to be the industry's first 15-sector 3G site are presented, showing further gains are possible well beyond the six sectors per site. [ABSTRACT FROM AUTHOR]

The Third-Generation Partnership Project (3GPP) has recently started standardizing the “licensed-assisted access using LTE” for small cells, which is referred to as dual-band femtocell (DBF) in this paper, which uses the Long-Term Evolution (LTE) air interface in both the licensed and unlicensed bands based on the LTE carrier aggregation feature. Alternatively, the Small Cell Forum introduced the integrated femto-WiFi (IFW) small cell, which simultaneously accesses both the licensed band (via cellular interface) and the unlicensed band (via WiFi interface). In this paper, a practical algorithm for IFW and DBF to automatically balance their traffic in licensed and unlicensed bands, based on the real-time channel, interference, and traffic conditions of both bands, is described. The algorithm considers the fact that some “smart” devices (sDevices) have both cellular and WiFi radios, while some WiFi-only devices (wDevices) may only have WiFi radio. In addition, the algorithm considers a realistic scenario where a single small-cell user may simultaneously use multiple sDevices and wDevices via either the IFW or the DBF in conjunction with a wireless local area network. The goal is to maximize the total user satisfaction/utility of the small-cell user, while keeping the interference from small cells to macrocells below predefined thresholds. The algorithm can be implemented at the radio link control or the network layer of the IFW and DBF small-cell base stations. Results demonstrate that the proposed traffic-balancing algorithm applied to either IFW or DBF significantly increases the sum utility of all macrocell and small-cell users, compared with the current practices. Finally, various implementation issues of IFW and DBF are addressed. [ABSTRACT FROM PUBLISHER]

Resource-constrained end devices can offload computation to backend clouds. The stochastic wireless channel that an end device is connected to can introduce bursty computation demand to the cloud. Specifically, under good channel conditions, a device can transmit more data to the cloud, which consequently yields higher instantaneous computation demand. Conversely, poor channel conditions can result in lower instantaneous demand. The performance indicator for such a mobile cloud computing system is the average of the response time, which is the time span from the arrival of the computation demand at the backend cloud instance to the completion of its execution. The question we target in this paper is how resources should be provisioned for the backend cloud instance to address this bursty computation demand and guarantee a desired quality-of-service (QoS), namely, a user-specified average response time. To answer this question, we model the mobile cloud computing system as two tandem queues. We analyze this queueing network using the fluid flow analysis framework, and derive the analytical relationship between the required resource capacity at the backend cloud instance and the desired QoS, given the workload generation process at the end device and the wireless channel conditions. Having obtained the required resource capacity for a desired QoS, we then determine whether it is economical to provision this resource capacity by subscribing to the traditional static instance or the recently introduced burstable instance offered by public cloud providers. Finally, trace-driven simulations validate our theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we study how to achieve network utility maximization (NUM) in flow-level wireless networks, which can be characterized by the random arrivals and departures of flow-level traffic in such networks. Existing work in this area has mainly concentrated on finding the stability region in such networks while achieving the NUM objective. In this paper, we propose a fully distributed adaptive CSMA based flow-level cross-layer resource allocation algorithm (FLRA), which achieves the NUM goal while satisfying desired delay requirement via optimized link scheduling at the MAC layer and optimal flow-level admission control at the transport layer. Detailed algorithm design is presented. We analyze the convergence property of FLRA and its optimality in terms of network utility while meeting desired delay requirement. We further reveal the relationship among maximum network utility, desired delay, and number of active flows when a network reaches stability. We conduct extensive simulations and the results validate the effectiveness of our analytical results. [ABSTRACT FROM AUTHOR]

Radio-frequency (RF) energy harvesting is one of the promising technologies in wireless networks. This paper considers wireless powered communication networks (WPCNs) where one hybrid access point (H-AP) coordinates RF energy/information transmissions to/from a set of nodes. For the important type of WPCNs where the nodes have throughput requirement, we aim to minimize H-AP's energy provision (EP) via jointly optimizing the time allocation of energy/information transmissions and H-AP's transmission power while satisfying node throughput requirement. More specifically, the half-duplex WPCN is considered first. We prove that H-AP's energy transmission power must be the maximum allowed value to achieve the minimal EP, then show that the problem is convex under this condition and finally design an algorithm applying golden section search and bisection search jointly to efficiently obtain the optimal time allocation. Second, the full-duplex WPCN is considered. Its EP minimization problem is proved convex. However, due to the hardness of solving it directly, we turn to solve the feasibility problem (FP) for a given EP per unit time. We construct a convex optimization problem based on this FP and design a dual subgradient algorithm for finding its optimal solution, which indicates whether this FP is feasible. The minimal EP per unit time and its corresponding optimal solution are found by using the bisection search method. Simulation results show that, the EP-minimized schemes are able to greatly reduce H-AP's EP as compared to the baseline schemes. [ABSTRACT FROM AUTHOR]

With the increasing demand of spectrum and emergence of mobile devices, a cloud radio access network (C-RAN) is a promising technology to improve network capacity and coverage. The key concept of the C-RAN is to separate the radio function unit in remote radio heads (RRHs) from the digital function unit in baseband units (BBUs). This separation facilitates efficient spectrum and infrastructure sharing in the C-RAN. This paper considers the cooperative interference management among RRHs in the C-RAN. The RRHs can form coalitions to mitigate intra-interference and jointly serve their subscribers. To characterize RRH performance under the coalition, this paper develops two signal-to-interference-plus-noise-ratio (SINR)-based downlink throughput models of RRH, where one adopts tools from stochastic geometry to capture the interference from vehicular users (VUs) belonging to noncooperative RRHs, and another ignores the VU interference. In this paper, a coalition formation game is formulated to model the situation in which RRHs of C-RAN can make an individual decision to cooperatively serve their VUs if the throughput of the RRH can be improved. To obtain the solution of the proposed game, we develop a distributed coalition formation algorithm and analyze the stability of the coalition structure using a Markov chain model. Simulation results show that, as compared with the noncoalition and grand coalition, our distributed coalition formation can improve the C-RAN throughput by at least 20% and 80%, respectively. Furthermore, according to extensive simulation, we can define the conditions needed for RRHs to form a coalition and obtain higher throughput. [ABSTRACT FROM PUBLISHER]

Vehicular ad hoc networks (VANETs) experience large-scale high-speed mobility and volatile topology. VANETs may therefore experience intermittent connections and may occasionally be unable to guarantee end-to-end connections. This gives the medium access control (MAC) layer the opportunity to adapt its transmission strategy to the current unstable wireless connections to improve transmission efficiency. In this paper, we propose an adaptive frame length aggregation scheme (AFLAS) for VANETs, which is designed to improve transmission efficiency and increase data throughput. In our scheme, the incoming data packets from higher layers are queued separately in the MAC layer to wait for transmission opportunities. Suitable aggregation frame lengths are calculated according to the current wireless status and applied in the MAC layer at the onset of data transmissions. In this paper, we analyze and apply our AFLAS strategy to two current frame aggregation schemes in IEEE 802.11. We also report on the performance evaluation of our scheme. Our results exhibit significant improvement results in data throughput, retransmissions, overheads, and transmission efficiency in comparison with nonadaptive aggregation schemes. [ABSTRACT FROM PUBLISHER]

The stochastic properties of vehicles’ arrival process and the high-speed mobility of vehicles lead to dynamic changes in the topology of vehicular networks, affecting the data download experience of users, especially for large files. In this paper, a novel elastic-segment-based vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) cooperative strategy (ESCS) is proposed to reduce the impact of the density of vehicles on achievable throughput. The achievable throughput and optimal parameters of the proposed system are analyzed. The strategy takes the impact of the density of vehicles on the data download process as the key element for consideration. The density of vehicles has a great influence on the distance between vehicles, and further affects the transmission data rate. To solve the problem of low transmission data rate induced by the density of vehicles, the sizes of the elastic-segments are optimized according to the distance between the vehicles. Owing to the stochastic process of the distance between vehicles, it is particularly challenging to derive a closed-form expression for the achievable throughput. To tackle this problem, we develop a new V2I/V2V cooperative model to adapt to the general two-way lanes, analyze the distribution and mobility of vehicles, and derive a closed-form expression for the achievable throughput, as a function of V2I effective transmission range, the V2V effective transmission range, and other system parameters. We then optimize V2V effective connection range and the vehicle density to maximize the achievable throughput. Simulation results show that the proposed strategy significantly improves the throughput compared with the existing cooperative strategy, especially in the scenario of high vehicle density. [ABSTRACT FROM AUTHOR]

Ultra-reliable low-latency communication (uRLLC) emerges as one of the three service categories in fifth-generation (5G) wireless networks, with a potential to support multiple advanced services for latency-sensitive communications. The inherent openness of the wireless environment makes security in 5G unprecedentedly urgent to be addressed. Accordingly, the physical layer security (PLS) technique exploits the randomness characteristics of the wireless channel to fulfill security and confidentiality of information transmission. Different from many current works, which ignored the significance of security in uRLLC, this paper studies secrecy improvement strategy design in uRLLC scenarios. First, we propose suitable performance metrics for evaluating PLS of uRLLC and make a compromise between reliability, latency, and security, while maximizing the network throughput. Next, we identify the key challenging issues for achieving PLS in the context of uRLLC, and discuss the role of cooperative communication and mobility in terms of possible solutions. To the best of our knowledge, this is the first paper to make a trade-off among reliability, security and network throughput. Simulations validate the theoretical analyses. [ABSTRACT FROM AUTHOR]

The performance evaluation of wireless systems is crucial for the development of future systems with more connected devices. It is essential to have an easy and relevant method for ensuring the wireless communication performance of the devices. We have recently developed a new random line-of-sight (random-LOS) measurement system for evaluating the communication performance of wireless devices, e.g., transceivers and antennas installed on a vehicle. In the measurement system, a plane wave is generated in the test zone emulating the far-field wave transmitted from a radio base station. In this paper we present both numerical simulations and actual experimental results of the random-LOS over-the-air (OTA) measurement setup operating in the 1.5–3 GHz band. The measurement accuracy is determined by the field variations within the test zone, where a smaller variation gives better measurement accuracy. In this paper the achieved accuracy expressed in terms of standard deviation (STD) was evaluated to be approximately 1 dB of the power within a cylindrical test zone of height 0.4 m and diameter 2 m. The active multiple-input multiple-output (MIMO) performance of antenna systems installed on an actual vehicle was measured and evaluated using the presented setup. A comparison to a theoretical zero forcing (ZF) receiver is also presented. [ABSTRACT FROM AUTHOR]

In this paper, the scaling law of the network throughput of a special type of heterogeneous networks is studied, where a secondary network composed of cognitive users shares the same resources opportunistically with a primary network of licensed users. Some pioneering works in this area showed that this type of heterogeneous networks performs as well as two stand-alone networks under the dense network model. A key assumption behind this conclusion is that the density of the secondary network is higher than that of the primary network in the order sense, which essentially decouples the two overlaid networks as the secondary network dominates asymptotically. In this paper, we endeavor to investigate this problem with a weaker condition that the dimensions of the two overlaid networks are on the same order, under the extended network model. Our analysis shows that, with the ratio of the two network sizes larger than a threshold, this weaker (and arguably more practical) condition does not degrade either network throughput scaling. Our result further reveals the potential of cognitive radio (CR) technology in real applications. [ABSTRACT FROM PUBLISHER]

Assuming noisy feedback channels, this paper investigates the data transmission efficiency and robustness of different automatic repeat request (ARQ) schemes using adaptive power allocation. Considering different block-fading channel assumptions, the long-term throughput, the delay-limited throughput, the outage probability, and the feedback load of different ARQ protocols are studied. A closed-form expression for the power-limited throughput optimization problem is obtained, which is valid for different ARQ protocols and feedback channel conditions. Furthermore, the paper presents numerical investigations on the robustness of different ARQ protocols to feedback errors. It is shown that many analytical assertions about the ARQ protocols are valid both when the channel remains fixed during all retransmission rounds and when it (in)dependently changes in each round. As demonstrated, optimal power allocation is crucial for the performance of noisy ARQ schemes when the goal is to minimize the outage probability. [ABSTRACT FROM PUBLISHER]

Mobile network caching (MNC) and Coordinated MultiPoint (CoMP) joint transmission (JT) techniques are expected to play a significant role in future networks. Yet, when considering caching in a CoMP-integrated network where both single transmission (ST) and JT are permitted, some challenges need to be tackled. In this paper, we propose a cooperative online caching strategy to realize autonomous transmission-aware content caching and updating for video content delivery. Different from existing works, this paper considers practical time-varying user request patterns, and exploits storage-level and transmission-level cooperation to jointly optimize content caching under dynamic user demands for JT and ST. The former helps reduce caching redundancy and the latter helps BSs create CoMP-JT opportunities to improve cell-edge throughput. We formulate the content caching problem to be a Markov decision process (MDP), in which the system reward is defined as the delay reduction after performing a caching action. The goal is to maximize the system reward. Then, we develop a reinforcement learning (RL)-based online learning algorithm to search the optimal caching policy. To overcome the “curse of dimensionality,” the designed RL-based algorithm is extended with linear approximation. The system performance in terms of delay and cache hit rate is evaluated in the simulations, and the results demonstrate the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

Radio spectrum sensing (SS) has been an active topic of research over the past years due to its importance to cognitive radio (CR) systems. However, in CR networks (CRNs) with multiple primary users (PUs), the secondary users (SUs) can often detect PUs that are located outside the sensing range, due to the level of the aggregated interference caused by the PUs. This effect, known as spatial false alarm (SFA), degrades the performance of CRNs because it decreases the SUs' medium access probability. This paper characterizes the SFA effect in a CRN, identifying possible actions to attenuate it. Adopting energy-based sensing (EBS) in each SU, this paper starts to characterize the interference caused by multiple PUs located outside a desired sensing region. The interference formulation is then used to write the probabilities of detection and false alarm, and closed-form expressions are presented and validated through simulation. The first remark to be made is that the SFA can be neglected, depending on the path-loss factor and the number of samples collected by the energy detector to decide the spectrum's occupancy state. However, it is shown that by increasing the number of samples needed to increase the sensing accuracy, the SUs may degrade their throughput, namely, if SUs are equipped with a single radio that is sequentially used for sensing and transmission (split-phase operation). Assuming this scenario, this paper ends by providing a bound for the maximum throughput achieved in a CRN with multiple active PUs and for a given level of PUs' detection inside the SUs' sensing region. The results presented in this paper show the impact of path loss and EBS parameterization on SUs' throughput and are particularly useful to guide the design and parameterization of multihop CRNs, including future ad hoc CRNs considering multiple PUs. [ABSTRACT FROM AUTHOR]

The small cells in millimeter wave (mmWave) have been utilized extensively for the fifth generation (5 G) mobile networks. And full-duplex (FD) communications become possible with the development of self-interference (SI) cancellation technology. In this paper, we focus on the optimal allocation of the sub-channels in the small cells deployed densely underlying the mmWave networks. In order to improve the resource utilization and network capacity, device-to-device (D2D) communications are adopted in networks. For maximizing the system throughput, we propose a cooperative sub-channel allocation approach based on coalition formation game, and theoretically prove the convergence of the proposed allocation algorithm. The utility of the coalition formation game is closely related to the sum system throughput in this paper, and each link makes an individual decision to leave or join any coalition based on the principle of maximizing the utility. Besides, a threshold of the minimum transmission rate is given to improve the system fairness. Through extensive simulations, we demonstrate that our proposed scheme has a near-optimal performance on sum throughput. In addition, we verify the low complexity of the proposed scheme by simulating the number of switch operations. [ABSTRACT FROM AUTHOR]

In a cognitive radio network (CRN), two nodes have a rendezvous when they tune to the same channel simultaneously. Providing rendezvous guarantee between any pair of nodes is essential because a rendezvous is necessary for communication. Some existing works claim that rendezvous guarantee can be provided by using a dedicated common control channel to negotiate the channel being used. A serious problem of these mechanisms is that a globally available channel may not exist. Some channel hopping protocols try to provide a rendezvous guarantee without using a common control channel. However, these solutions may suffer from a poor number of rendezvous or uneven channel utilization. In this paper, we propose a novel distributed channel hopping protocol: Quorum and Latin square channel hopping (QLCH). The QLCH scheme efficiently provides rendezvous guarantee by utilizing the concept of quorum systems and Latin squares. The former is utilized to guarantee balanced rendezvous among nodes, whereas the latter is adopted to share the rendezvous among channels. QLCH efficiently provides fast rendezvous guarantee and can cooperate with other channel hopping protocols to enhance network throughput. Analytical and simulation results verify the improvement of QLCH. For example, when there are 30 flows using 11 channels in a CRN, the achieved time to rendezvous of QLCH is 9.84 times lower than that of the existing protocol SYNC-ETCH, whereas the achieved network throughput of QLCH is 362% higher than that of the existing protocol, i.e., Quorum-based channel hopping (L-QCH). [ABSTRACT FROM PUBLISHER]

In this paper, the throughput maximization of millimeter-wave (mm-Wave) ultradense networks (UDN) using dynamic spectrum sharing (DSS) is considered. Most of the existing works only allow temporal-domain access and admit at most one user at each time slot, resulting in significant underutilization of spectrum resource, which will be less attractive to mm-wave UDN applications. A generalized temporal-spatial sharing scheme is proposed in this paper for UDN by exploiting the location information of incumbent devices, where multiple users are allowed to access each channel simultaneously via spatial separations. For distributed applications, the global information exchange among secondary users (SU) tends to be impractical, given the unaffordable signaling overhead and latency. Thus, a noncooperative game with fine-grained two-dimensional reuse is formulated, which leads to a more efficient access strategy. It is then proved to be an ordinary potential game (OPG), which guarantees the existence of the strategy Nash equilibrium (NE). Finally, an improved decentralized reinforcement learning algorithm is designed, with which SUs can learn from wireless environments and adapt toward an NE point, relying on the individual observation and the historical action reward (rather than the global information exchanging). The convergence efficiency of the new scheme is also rigorously proved. Numerical simulations are provided to validate the performances of the proposed schemes. [ABSTRACT FROM AUTHOR]

With the explosive growth of vehicle applications, vehicular networks based on millimeter wave (mmWave) bands have attracted interests from both academia and industry. mmWave communications are able to utilize the huge available bandwidth to provide multiple Gbps transmission rates among vehicles. In this paper, we address the content distribution scheduling problem in mmWave vehicular networks. It has been challenging for all vehicles in the same network to complete content downloading due to the limited communication resources of roadside units (RSUs) and the high mobility of vehicles. We propose a joint vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) scheduling scheme to minimize the total number of content distribution time slots from a global optimization perspective. In the V2I phase, the RSU serially transmits integrity content to vehicles, which are selected according to the vehicular network topology and transmission scheduling scheme. In the V2V phase, full-duplex communications and concurrent transmissions are exploited to achieve content sharing between vehicles and improve transmission efficiency. Performance evaluations demonstrate that our proposed scheme reduces the number of time slots and significantly improves system throughput when compared with other schemes, especially under large-size file transfers and a large number of vehicles. [ABSTRACT FROM AUTHOR]

Mobile edge computing (MEC) has recently risen as a promising paradigm to meet the increasing resource requirements of the terminal devices. Meanwhile, small cell network (SCN) with MEC has been emerging to handle the exponentially increasing data traffic and improve the network coverage, and is recognized as one key component of the next generation wireless networks. However, with the growing number of terminal devices requiring computation offloading to the edge servers, the network would be heavily congested and thus the performance would be degraded and unbalanced among multiple devices. In this paper, we propose the joint admission control and computation resource allocation in the MEC enabled SCN, and formulate it as a stochastic optimization problem. The goal is to maximize the system utility combining the throughput and fairness while bounding the queue. We decouple the original problem into three independent subproblems, which can be solved in a distributed manner without requiring the system statistical information. An admission control and computation resource allocation (ACCRA) algorithm is designed to obtain the optimal solutions of the subproblems. Theoretical analysis proves that the ACCRA algorithm can achieve the close-to-optimal system utility and reach the arbitrary tradeoff between the utility and the queue length. Experiments are conducted to validate the derived analytical results and evaluate the performance of the ACCRA algorithm. [ABSTRACT FROM AUTHOR]

Free-space optics (FSO)-based, low-earth orbit (LEO) satellite-assisted Internet of vehicles (IoVs) has recently attracted research efforts worldwide. For the majority of Internet applications, transmission control protocol (TCP) is one of the most widely deployed protocols. Nevertheless, a complete understanding of the TCP performance over FSO-based satellite-assisted IoVs networks is still lacking in the literature. This is a highly challenging issue, as a consequence of the non-trivial interdependencies between transmission losses caused by the dynamics/uncertainty of atmospheric last-mile channels and the buffer overflows on the Internet, as well as their joint impact on the TCP congestion control mechanisms. This paper offers a comprehensive analytical framework that allows assessing the TCP throughput performance under the joint impact of congestion losses occurred in the Internet and transmission errors at the last-mile link from the satellite-to-vehicle. Internet access for emerging unmanned aerial vehicles (UAVs) is considered while the analysis can be also applied to other kinds of vehicles, which, in fact, require simpler channel models. The link-layer incremental redundancy hybrid automatic repeat request (IR-HARQ) protocol is employed at satellite-to-UAV channels to further improve the TCP throughput performance. Numerical results provide non-trivial findings and insights for the TCP performance in satellite/FSO-based IoVs, in which optimal UAV’s parameters are chosen to maximize the TCP throughput. [ABSTRACT FROM AUTHOR]

This paper proposes a novel bit loading algorithm to multicarrier non-orthogonal multiple access (NOMA) systems to maximize the system total throughput while satisfying the users’ individual quality of service (QoS) constraints. Although bit loading is generally a non-deterministic polynomial-time (NP)-hard problem, even for orthogonal multiple access (OMA), the mutual interference between the users, and the dependence of power coefficients and modulation orders are additional challenges that add substantial complexity to the optimization problem. Therefore, in this paper, we propose an efficient bit loading algorithm for multicarrier NOMA systems and compare the complexity and throughput with a corresponding OMA system. The obtained results show that for the case of NOMA, bit loading provides an additional degree of freedom that allows non-uniform spectrum sharing among the users. In particular scenarios, the system may experience hybrid modes of operation, where the system switches between NOMA and OMA. The obtained numerical results show that NOMA can outperform OMA by 100% in terms of spectral efficiency, for a two-user scenario. The complexity of the loading process for NOMA is noticeably higher than OMA, which is due to the high complexity associated with the bit error rate (BER) computation in the case of NOMA. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the tradeoff design between communication and radar detection for a joint communication and radar (CommRadar) system by leveraging a low-complexity hardware architecture. To achieve this, we exploit the communication traffic diversity to design an adaptive scheduling policy. Through adjusting the CommRadar mode selection, radar steering direction and communication user scheduling, and time allocation between communication and radar detection, we could better utilize the un-occupied transmission time to improve radar detection performance when the data traffic is light, and balance the time allocation between communication and radar detection when the data traffic is heavy. Moreover, for our adaptive scheduling method, we have provided a quantitative performance bound for data throughput, queueing delay, and radar detection performance of both short-term and long-term. By conducting extensive simulation studies, we have demonstrated that our method could greatly reduce the communication performance loss when integrating the radar functionality, while still guaranteeing radar detection performance. [ABSTRACT FROM AUTHOR]

Driven by the massively growing applications in Internet of Things (IoT) and the new requirements of the six generation (6G) wireless network, the amount of terrestrial mobile devices (TMDs) and data traffic in wireless communications have increased explosively. Consequently, the integrated terrestrial-satellite relay networks (ITSRNs) have emerged to address the issue of the huge wireless traffic with limited allocated resources, which attracts extensive research attention to the field of IoT. Limited improvement of system throughput is realized by configuring terrestrial relays (TR) in the previous works. In this paper, by introducing an aerial relay (AR), we propose a novel structure of ITSRN and investigate the system throughput maximization and energy consumption minimization problems by jointly optimizing power allocation and AR altitude. Specifically, the system implementation includes two periods: satellite to relay (S-R) period and satellite to devices (S-D) period. To maximize the overall system throughput, we propose a joint optimization scheme of the power allocation and altitude of AR. Due to its non-convexity, a bilevel programming method is proposed to obtain the global optimal solution, where the closed-form expressions of power allocation and the optimal altitude of AR are derived. Subsequently, we investigate the energy consumption minimization problem during S-R period, which is formulated as a convex problem. We propose a low complexity algorithm and derive the optimal closed-form solution based on the rigorous mathematical analysis. The effectiveness of the proposed algorithms and solutions are verified by extensive simulations. [ABSTRACT FROM AUTHOR]

The explosively increasing traffic demand in the fifth generation (5 G) mobile communication system has made the limited licensed spectrum quite competitive. Such status quo motivates the development of new radio (NR) based access to the unlicensed band, which is a promising solution for system performance enhancement. In this paper, we focus on the coexistence between the NR system and the WiFi system based on the duty cycle mechanism. Firstly, an optimization model is formulated to maximize the throughput of the NR system in the unlicensed band (NR-U) via the joint bandwidth and transmission opportunity allocation under the fairness requirement. Then, to solve this optimization problem, we convert it into a Markov decision process with continuous action space, based on which a deep deterministic policy gradient (DDPG) based coexistence algorithm is proposed. At last, simulation results show that the proposed algorithm can ensure the coexistence between the NR-U system and the WiFi system from three aspects. Firstly, the throughput improvements of the NR-U system under different fairness thresholds and different number of user equipments and access points are illustrated. Secondly, the proposed algorithm adapts to the dynamic situations of varying fairness thresholds and channel conditions. Thirdly, the effectiveness of the proposed algorithm is validated with at least 5.01% throughput improvement by comparing with proportional scheme, average scheme and Q-learning scheme. [ABSTRACT FROM AUTHOR]

Cellular heterogeneous networks (HetNets), which are realized through shared carrier deployments of macrocells and small cells, are widely seen as a potential solution to serve growing data capacity demands. While these networks pose significant challenges in interference management, much of the focus in earlier efforts has been limited only to small-cell range expansion in the downlink. In this paper, we provide a comprehensive analysis of interference management techniques applicable to the uplink of cellular HetNets, with the goal of characterizing and improving edge user (e.g., 5th percentile) performance. In particular, we propose and study virtual soft-handoff (VSHO), which offers a low-complexity and low-overhead solution that exploits the link asymmetry observed in the uplink geometry of HetNets. VSHO exploits the fact that, in the uplink, an edge macro user who suffers from very low throughput may be closer to a nearby small cell than its own macrocell. The intuition is that such macro users should have better decoding opportunity when their signals are processed at the nearby small cell with better channel conditions. We also study how interference cancelation (IC) and interference avoidance through resource blanking can be incorporated into our VSHO proposal for further throughput gains. In addition to the VSHO techniques outlined in this paper, we also analyze other candidate techniques available in the Third Generation Partnership Project Long-Term Evolution (3GPP-LTE), such as cell-range expansion (CRE) and joint processing, to present a unified view of interference management options available in HetNets. [ABSTRACT FROM PUBLISHER]

Millimeter-wave (mmWave) cellular systems are power limited and susceptible to blockages. One promising approach to increasing mmWave connectivity and range is to use relays. Device-to-device (D2D) communications open the door to the vast opportunities of D2D relaying for mmWave cellular systems. In this paper, we study how to select a good relay for a given source–destination pair in a two-hop mmWave cellular system, where the mmWave links are subject to random Bernoulli blockages. In such a system, probing more relays could potentially lead to the discovery of a better relay but at the cost of more overhead. We find that the throughput-optimal relay probing strategy is a pure threshold policy: The system can stop relay probing once the achievable spectral efficiency of the currently probed two-hop link exceeds an optimized threshold. We further characterize the optimal spectral efficiency threshold via a fixed-point equation. [ABSTRACT FROM PUBLISHER]

Unmanned aerial vehicle (UAV) swarm has emerged as a promising novel paradigm to achieve better coverage and higher capacity for future wireless network by exploiting the more favorable line-of-sight (LoS) propagation. To reap the potential gains of UAV swarm, the remote control signal sent by ground control unit (GCU) is essential, whereas the control signal quality are susceptible in practice due to the effect of the adjacent channel interference (ACI) and the external interference (EI) from radiation sources distributed across the region. To tackle these challenges, this paper considers priority-aware resource coordination in a multi-UAV communication system, where multiple UAVs are controlled by a GCU to perform certain tasks with a pre-defined trajectory. Specifically, we maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all the UAVs by jointly optimizing channel assignment and power allocation strategy under stringent resource availability constraints. According to the intensity of ACI, we consider the corresponding problem in two scenarios, i.e., Null-ACI and ACI systems. By virtue of the particular problem structure in Null-ACI case, we first recast the formulation into an equivalent yet more tractable form and obtain the global optimal solution via Hungarian algorithm. For general ACI systems, we develop an efficient iterative algorithm for its solution based on the alternating optimization methods. Extensive simulation results demonstrate that the proposed algorithms can significantly enhance the minimum SINR among all the UAVs and adapt the allocation of communication resources to diverse mission priority. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the joint sub-channel and power allocation problem for cellular vehicle-to-everything (V2X) communications, where multiple vehicle-to-infrastructure (V2I) users share the spectrum resources with vehicle-to-vehicle (V2V) users. In particular, a novel channel state information (CSI)-independent decentralized algorithm based on multi-agent reinforcement learning (MARL) is proposed to maximize the sum throughput of V2I links while meeting the latency and reliability requirements of V2V links. Specifically, we implement the individual double dueling deep recurrent Q-networks (D3RQN) and the carefully designed common reward to train the implicitly collaborative agents, through which, each agent optimizes the policy individually based solely on local CSI-independent observations. To handle the non-stationarity induced by multi-agent concurrent learning, we incorporate hysteretic Q-learning and concurrent experience replay trajectory (CERT) to stabilize the training process. Besides, we incorporate the approximate regretted reward (ARR) to alleviate the unstable reward estimation problem caused by shifting environment dynamics. Simulation results demonstrate that the proposed algorithm outperforms the baselines and can achieve close performance compared with the centralized Brute-force method. Furthermore, the proposed CSI-independent design exhibits comparable performance as the CSI-involved version, which sheds some light on the potential to further reduce the signalling overhead of machine learning-based vehicular communication systems. [ABSTRACT FROM AUTHOR]

LTE LAA listen-before-talk (LBT) procedures have been considered a promising solution to reasonable coexistence of LTE with other access technologies in unlicensed spectrum. An issue that arises with the LAA LBT procedures is the so-called GAP period, which may largely degrade the performance of a coexistence system. There are two methods to deal with the GAP period. Method 1 is to fill in the channel during a GAP period by using a reservation signal, while Method 2 takes no action but just listens to the channel during a GAP period. Most existing analytical models for the LAA LBT procedures are inaccurate because they do not take into account the GAP period. This paper studies the modeling of the LAA category-4 LBT procedure in an LAA and WiFi coexistence system and investigate the impact of the GAP period on the system performance. A 2-D Markov chain is built to model the category-4 LBT procedure of an LAA eNodeB, considering the effect of the GAP period. Based the Markov model, analytical models are further derived to investigate the throughput and packet delay performance of the coexistence system with Method 1 and Method 2, respectively. Numerical results show that with Method 1, the performance of an LAA eNodeB is similar to that of a WiFi AP in terms of the transmission probability and packet delay. With Method 2, the performance of an LAA eNodeB is worse than that of a WiFi AP. [ABSTRACT FROM AUTHOR]

To meet the ever-increasing demand for mobile data traffic, mobile operators are seeking to utilize unlicensed spectrum as a supplement to the licensed spectrum. The harmonious and spectrum-efficient coexistence scheme between LTE and incumbent users on the unlicensed spectrum is thus mandatory. Currently, advanced intelligent technologies are being expected to play the crucial role in the future communication system. We thus introduce the Q-learning (QL) framework into LTE licensed assisted access (LAA) scheme in the paper, thereby forming a QL based LAA scheme. We first redefine the fairness in the sharing of unlicensed spectrum and then divide the state space into six states based on the predefined throughput and fairness thresholds, followed by the definition of the action set and reward function. In the proposed scheme, based on the convergent Q table, where each element is used to evaluate the pros and cons of taking an action, the agent can repeatedly interact with the environment until it reaches the terminal state, i.e. selects the optimal action (i.e. contention window size). Additionally, the chaotic motion with ergodicity, regularity and randomness is first introduced into the action-decision strategy to accelerate the training velocity with the balance consideration of exploration and exploitation. The simulation results prove that the proposed $\epsilon$ -chaotic greedy selection strategy has faster convergence velocity compared with other methods such as $\epsilon$ -greedy, pure greedy, Bolzmann and random selection strategy, and that the proposed chaotic QL LAA scheme outperforms the other LAA schemes such as the 3GPP, linear, fixed LAA and Listen Before Talk (LBT) adaptive schemes in terms of throughput, collision probability, fairness and delay. [ABSTRACT FROM AUTHOR]

This correspondence paper investigates uplink non-orthogonal multiple access (NOMA) for unmanned aerial vehicle base stations (UAV-BSs). Users under the service area of a UAV-BS perform NOMA random access (RA) by controlling their transmit power so that the UAV-BS can receive one of two predefined power levels. This facilitates successive interference cancellation (SIC) at the UAV-BS. This correspondence paper shows the maximum stable throughput of uplink NOMA RA in terms of the altitude and beamwidth of the UAV-BS. Further, we propose a stabilizing algorithm, with which a UAV-BS broadcasts the throughput-maximal retransmission probability every slot, while users access the channel based on the retransmission probability. Extensive simulations show that the proposed algorithm can achieve the maximum throughput 0.5869 (packets/slot) and stabilize the system with time-varying traffic. [ABSTRACT FROM AUTHOR]

This paper proposes and investigates a cooperative non-orthogonal multiple access scheme that is based on spectrum sensing (CNOMA-SS), where the primary user intends to communicate with the base station by the assistance of the secondary user. On the other hand, the secondary user can obtain an additional opportunity to access the spectrum band originally belonging to the primary user. Therefore, a win–win situation is achieved by our collaboration scheme. When employing the proposed scheme, the secondary user, i.e., the user relay, adopts the spectrum sensing technique to perceive the surrounding wireless environment by identifying the spectrum holes. According to the sensing results, the secondary user will intelligently determine its transmission signal form, eventually improving the overall system capacity. In this paper, we take the practical assumption of imperfect spectrum sensing into consideration. To characterize the performance of the proposed CNOMA-SS scheme, closed-form expressions for outage probability, system throughput in delay-limited transmission mode, ergodic rate, and system throughput in delay-tolerant transmission mode are derived, with or without the direct link between the base station and the primary user. Simulation results further validate these closed-form derivation expressions, verify the effectiveness of employing the spectrum sensing technique, and illustrate the superior performance of CNOMA-SS compared with two cooperative benchmarks, in terms of system throughput in delay-limited and delay-tolerant transmission modes with or without the direct link, respectively. [ABSTRACT FROM AUTHOR]

This paper considers the bit loading problem for communication systems that utilize orthogonal frequency division multiplexing (OFDM) in conjunction with precoding (POFDM) or time-domain interleaving (IOFDM). In particular, we propose a new bit loading algorithm for P/I-OFDM that has substantially higher effective throughput and less computational complexity, when compared to bit loading in conventional OFDM systems. The obtained results show that the effective throughput of P/I-OFDM can be more than fourfold the conventional OFDM while the complexity is less than $1.5\%$. Moreover, the results show that the peak-to-average power ratio (PAPR) properties of the considered systems are preserved under the adaptation process. [ABSTRACT FROM AUTHOR]

This paper considers random access in a communication channel, which is shared by $N$ active users with saturated traffic. Following a slotted ALOHA-type protocol, each active user attempts to transmit in every slot with a common probability. It is assumed that the channel has the multiple-packet reception capability to enable the correct reception of up to $M$ ($1 \leq M < N$) time-overlapping transmissions. To support mission- and time-critical applications that require reliable delivery within a strict delivery deadline $D$ (in units of slot), the aim of this paper is to achieve the maximum deadline-constrained reliability. First, we prove the uniqueness of the optimal transmission probability for any $1\leq M< N$ and any $D\geq 1$. Second, we show it can be computed by a fixed-point iteration for all the cases. Third, for real-life scenarios where $N$ may be unknown and changing, we develop a distributed algorithm for $M>1$ , which allows each active user to dynamically tune its transmission probability based on a method for estimating $N$. Simulation results verify our analysis and show that the proposed tuning algorithm is effective with near-optimal performance. In addition, as a special case (i.e., $D=1$) of our study, the issue of saturation throughput maximization is completely addressed for the first time. [ABSTRACT FROM AUTHOR]

The restricted resources of mobile wireless networks such as limited bandwidth have resulted in stringent requirements on the available quality of service (QoS). To enhance the communication performance, mobile nodes attempt to optimize the available bandwidth of wireless networks, which, however, makes them vulnerable to the malicious attacks of adversaries owing to the open and mobile context. Furthermore, improving the security level of the communication consumes bandwidth and thus degrades the communication quality. In order to harmonize the QoS and security, in this paper, the two conflicting terms “communication player” and “security player” are considered as two individual players and are balanced using game theory. Furthermore, we construct a non-cooperative game model, wherein the utilities of the communication player and security player are maximized by controlling the number of nodes transmitted and the length of hash, respectively. We formulate the utility functions of the communication player with respect to the throughput as well as the security level of the Merkle tree for the security player. This paper considers complete information game and incomplete information game, for which we theoretically determine the pure strategy Nash equilibrium and the pure strategy Bayesian Nash equilibrium, respectively. Extensive numerical calculations are performed to comprehensively investigate the utilities of each player and the Nash equilibrium for various combinations of the concerned parameters. The results show that the presented theoretical game approach enables a mobile node to adaptively perform specific actions based on the derived Nash equilibrium. With the obtained Nash equilibrium values, both communication player's and security player's utilities reach to the maximum so that satisfactory communication quality can be realized without compromising the security. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is increasingly becoming very attractive in cloud radio access networks (CRANs) to further boost the overall spectral efficiency, connectivity and, capacity of such networks. This paper addresses optimizing the energy efficiency (EE) for the downlink of a NOMA-based two tiers CRAN. The stochastic geometry represented by Poisson Point Process (PPP) distribution is used to decide the number and locations of the base stations (BSs) in each tier within the coverage area. A numerical optimal solution is obtained and compared against a proposed subgradient solution, as well as another proposed unoptimized solution based on the false positioning method. For comparison purposes, two other power allocation techniques are presented to allocate different powers to various BS categories; one allocates the power to each BS based on their relative distances to the cloud-based central station and the other is the bisection based scheme. Two simulation scenarios are presented to examine the performance of the two-tier NOMA-CRANs with NOMA is adopted as the multiple access of each tier in both cases. The first scenario considers heterogeneous CRAN (NOMA-HCRAN) case by using two different BS categories in each tier, namely, the macro-BSs and the RRHs. The second scenario considers a homogeneous CRAN (NOMA-CRAN) case by using the RRHs in both tiers but each tier has different frequency layer to prevent cross tier interference. Simulation results show the promising performance gain can be achieved with the proposed techniques relative to the existing approaches. More specifically, it was illustrated that the proposed subgradient based NOMA CRAN offers better performance than the proposed false positioning based NOMA CRAN, which is in turn better than the existing techniques, in particular, the bisection and the distance based NOMA-CRAN. [ABSTRACT FROM AUTHOR]

With low-density parity-check (LDPC) codes and polar codes selected as the standard codes for the fifth generation (5 G) enhanced Mobile Broad Band scenario (eMBB), a decoding architecture that can simultaneously support the decoding of control and data plane becomes necessary at the terminal side to meet the raising requirement for 5 G network deployment. Due to the special structure of LDPC codes according to the Release 15 (R15) 5 G standard, a straight-forward extension of the existing reconfigurable scheme is in general difficult. Therefore in this paper, a unified decoding architecture is proposed that can be reconfigured to either LDPC codes or polar codes. Due to various differences between the two codes such as parity-check matrices, codeword lengths and iterative methods, a joint decoding algorithm is introduced by reordering basic decoding operations to the unified add-comparison-add pattern for both codes. Then, a pipelined structure of reconfigurable decoding unit (RDU) is presented correspondingly which is fully compatible with all decoding patterns of the R15 standard. And finally, a reconfigurable decoder is proposed with multiple levels of parallelism, and the reconfiguration scheme is introduced to improve the hardware utilization and decoding efficiency. The proposed decoder is implemented in FPGA and ASIC, respectively, and has achieved state-of-the-art performance in throughput and area efficiency compared to LDPC-only and polar-only decoders. [ABSTRACT FROM AUTHOR]

In this paper, we derive an upper bound on load-threshold of coded slotted ALOHA (CSA) for slot erasure channel (SEC) and that for packet erasure channel (PEC), respectively. In SEC, by exploiting the analogy between Gaussian elimination of solving linear equations and the iterative successive interference-cancellation (SIC) decoding procedure of CSA, we derive the upper performance bound for SEC. Subsequently, in PEC, utilizing density evolution to track the average probability of packet-decoded failure within the SIC decoding process, we obtain the upper bound for PEC. Moreover, we propose a numerical search algorithm of these bounds under a given calculating precision. The numerical results indicate that the asymptotic upper limit on load-threshold of CSA over SEC is always less than that over PEC with any given erasure probability and average transmission rate. [ABSTRACT FROM AUTHOR]

Control- and user-plane separation (CUPS) and network slicing are two key technologies to support increasing network traffic and diverse wireless services. However, the benefit of CUPS in decoupling the network coverage and data service functions has not been fully utilized to facilitate network slicing. In this paper, we present a novel CUPS-based end-to-end (CUPS-E2E) network slicing scheme. First, the base stations (BS) are classified into control BSs (CBS) that provide control plane (CP) coverage and traffic BSs (TBS) that deliver user plane (UP) traffic. Next, upon CBSs and TBSs being virtualized, we define four typical end-to-end (E2E) network slices: one for CP coverage, one for high-throughput services, one for computation-intensive services, and the other for delay-sensitive services. The utilities of the four E2E network slices are defined based on their coverage, throughput, computing capability and delay requirements, respectively. Then, a deep deterministic policy gradient (DDPG)-based algorithm is employed to maximize the long-term sum-utility of the four E2E network slices by jointly optimizing the allocation of communication and computing resources to the four network slices and the activation of virtual TBSs, while meeting the service requirements of all users. Simulation results show that our proposed CUPS-E2E network slicing scheme in conjunction with a DDPG-based sum-utility maximization algorithm can support the CP wide-coverage and massive access requirements as well as the UP high-throughput, computation-intensive and delay-sensitive services simultaneously, and outperforms the existing E2E network slicing schemes in terms of the sum-utility, coverage percentage, throughput and delay. [ABSTRACT FROM AUTHOR]

In this paper, we consider a general centralized feedback model for interference alignment (IA) algorithms of which precoders and decoders are designed with quantized channel state information (CSI) at a central unit and then fed back to corresponding transmitters and receivers via finite-rate links. The significant difference of this model from existing models is that all the realizations of channels, precoders, and decoders are fed back by finite rates. The signal-to-interference-plus-noise ratio (SINR) characteristic of this model is analyzed, which helps derive an upper bound of average throughput loss relative to perfect IA. The upper bound is shown to be tight by simulation, particularly in the high-feedback regime. Based on this result, the scaling laws of feedback bits for channels, precoding, and decoding vectors to obtain full degree of freedom are derived, which are backward compatible to the existing results for quantized CSI only or quantized precoder only. Simulation results show that the system is interference limited at a high signal-to-noise ratio (SNR) if the three scaling laws are not simultaneously satisfied, and the throughput performance is dominantly limited by the worst feedback links among the channels, precoders, and decoders. [ABSTRACT FROM PUBLISHER]