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This paper studies multi-agent deep reinforcement learning (MADRL) based resource allocation methods for multi-cell wireless powered communication networks (WPCNs) where multiple hybrid access points (H-APs) wirelessly charge energy-limited users to collect data from them. We design a distributed reinforcement learning strategy where H-APs individually determine time and power allocation variables. Unlike traditional centralized optimization algorithms which require global information collected at a central unit, the proposed MADRL technique models an H-AP as an agent producing its action based only on its own locally observable states. Numerical results verify that the proposed approach can achieve comparable performance of the centralized algorithms. [ABSTRACT FROM AUTHOR]

This paper investigates subchannel allocation based on clustered interference alignment in dense small cell networks when all small cell user equipments (SUEs) have differentiated requirements for data streams. By imposing the condition that each cluster has a size not exceeding the maximum value achieved when each SUE needs only one data stream, we maximize the number of SUEs with guaranteed requirements for data streams, which is NP-hard. Hence, we propose a two-phase efficient solution with much lower complexity and reduced feedback overhead. First, similarity clustering is performed by graph partition, and then, subchannel allocation is done through a coloring algorithm. Numerical results show that the proposed solution offers a performance better than the related schemes and close to the approximate optimal solution. [ABSTRACT FROM AUTHOR]

In this paper, we exploit the cooperative transmission as a new energy supply to support backscatter communication (BackCom), where there are multiple decode-and-forward (DF) relays and only one relay is selected in the cooperative system. The tag circuit power and signal backscattering are respectively supported by transmit powers of the source and the relay, and the minimum mean square error (MMSE) detector is employed at the receiver of the BackCom user to mitigate the interference from the cooperative system. Our objective is to maximize the quality of service (QoS) of the BackCom user which satisfying the QoS of the cooperative system, the total power constraint on the cooperative system and the harvested power constraint on the BackCom user. The probability of feasibility conditions, and optimized joint relay selection and power allocation are investigated in closed-form expressions. The zero forcing (ZF) detection and its comparison with the MMSE detection in the considered system are also analyzed. Simulation results demonstrate the benefit of the proposed scheme compared with traditional ones. [ABSTRACT FROM AUTHOR]

The millimeter wave (mmWave) communication has drawn intensive attention with abundant band resources. In this paper, we consider the popular content distribution (PCD) problem in the mmWave vehicular network. In order to offload the communication burden of base stations (BSs), vehicle-to-vehicle (V2V) communication is introduced into the PCD problem to transmit contents between on-board units (OBUs), and improve the transmission efficiency. We propose a full-duplex (FD) cooperative scheme based on coalition formation game, and the utility function is provided based on the maximization of the number of received contents. The contribution of each member in the coalition can be transferable to its individual profit. While maximizing the number of received contents in the fixed time, the cooperative scheme also ensures the individual profit of each OBU in the coalition. We evaluate the proposed scheme by extensive simulations in mmWave vehicular networks. Compared with other existing schemes, the proposed scheme has superior performances on the number of possessed contents, and system fairness. Besides, the low complexity of the proposed algorithm is demonstrated by the switch operation number, and CPU time. [ABSTRACT FROM AUTHOR]

In multi-user downlink small cell networks, cooperative resource allocation (RA) within a small cell cluster is a key technique to enhance network capacity. However, capacity-maximizing RA in frequency-selective fading channels requires global channel state information (CSI) of users within a small cell cluster, which makes it infeasible in practical networks with limited direct link capacity. To circumvent this global CSI assumption, most of the existing studies on RA have been based on several CSI assumptions such as local CSI and local CSI at the transmitters (CSIT). Nevertheless, cost functions with local CSI or local CSIT in the literature rely on heuristic formulations, because the sum-rate cannot be computed if without global CSI. In this paper, we propose a deep reinforcement learning-based RA algorithm to maximize the sum-rate for any given limited information on instantaneous CSI or sum-rate at the previous period. The proposed scheme is not restricted to certain CSI assumptions, but attempts to find the best RA for any given information such as quantized local CSI and quantized local CSIT; thus, it is applicable to any given direct link capacity. The proposed algorithm is self-adaptive in time-varying channels, since it is not divided into training and test phases. We modify the target neural network (TNN) scheme to enhance the sum-rate and the convergence speed. Numerical simulations confirm that: i) the proposed algorithm outperforms the conventional algorithms even under the same CSI assumption such as local CSI and local CSIT; ii) a flexible trade-off between the amount of CSI and the sum-rate is realizable in practical systems. [ABSTRACT FROM AUTHOR]

Combining intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) is an effective solution to enhance communication coverage and energy efficiency. In this paper, we focus on an IRS-assisted NOMA network and propose an energy-efficient algorithm to yield a good tradeoff between the sum-rate maximization and total power consumption minimization. We aim to maximize the system energy efficiency by jointly optimizing the transmit beamforming at the BS and the reflecting beamforming at the IRS. Specifically, the transmit beamforming and the phases of the low-cost passive elements on the IRS are alternatively optimized until the convergence. Simulation results demonstrate that the proposed algorithm in IRS-NOMA can yield superior performance compared with the conventional OMA-IRS and NOMA with a random phase IRS. [ABSTRACT FROM AUTHOR]

Ambient backscatter communication (AmBC) over orthogonal-frequency-division-multiplexing (OFDM) signals has recently been proposed as an appealing technique for low power Internet-of-Things (IoT) applications. The special spectrum structure of OFDM signals provides a range of flexibility in terms of bit-error-rate (BER) performance, data rate, and power consumption. In this paper, we study subcarrier-wise backscatter communication over ambient OFDM signals. This new AmBC is to exploit the special spectrum structure of OFDM to transmit data over its squeezed orthogonal subcarriers. We propose a basis transmission scheme, and its two modifications to support a higher data rate with superior BER performance compared to existing methods. The basis scheme can transmit one bit per subcarrier using on-off keying (OOK) modulation in the frequency domain. In the first modification, interleaved subcarrier block transmission model is employed to improve the BER performance of the system in frequency-selective channels. It results in a trade-off between the size of the blocks, and data rate. Thus, in the second modification, interleaved index modulation (IM) is employed to mitigate the data rate decrementation of the former modification. It also stabilizes, and controls the power of the signal to result in interference reduction for a legacy receiver. Analytical, and numerical evaluations provide a proof to see the performance of the proposed method in terms of BER, data rate, and interference. [ABSTRACT FROM AUTHOR]

Smart, and green cities impose stringent requirements on spectral efficiency (SE), and energy efficiency (EE) of vehicular networks. For the current vehicular ad-hoc networks (VANETs), vehicle's mobility leads to rapid topology changes, and high channel uncertainty. However, clustering schemes for establishing stable clusters, and robust power control (RPC) combating with channel fluctuation are investigated independently. In this paper, joint clustering, and RPC schemes are proposed to optimize the SE, and EE of the involved VANETs. Via the same fixed-length slot, the synchronized interference constraints of cluster heads (CHs) are formed, and offer conditions for RPC. Due to the random channel fluctuations, all CHs’ synchronized interference constraints are formulated as probability constraints. Besides, a pricing-based utility which avoids the separate optimization between SE, and EE is introduced, and the price's impact on the tradeoff between them is involved. Since the probability constraints are intractable, and the unified utility is nonconvex, the Bernstein approximation, and successive convex approximation (SCA) are used to transform the problem into a tractable convex one. Through dual decomposition, two RPC algorithms are proposed to determine the optimal solutions for the fixed price C, and the optimal price C*, respectively. Numerical simulations are used to evaluate the algorithmic performances in high-dynamic system, and the results show that the proposed algorithms are effective. The validity of the clustering method, and the proposed RPC scheme is further verified by comparisons. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of a non-orthogonal multiple access (NOMA) network with simultaneous wireless information, and power transfer (SWIPT) based battery-assisted energy harvesting (EH) full-duplex relay (FDR). In each signalling interval, the base-station communicates directly to a near user (NU), and through an EH FDR to a far user (FU). Considering the power-splitting (PS) protocol with a non-linear EH model, we derive closed-form expressions for the NU, and FU outage probabilities. We also demonstrate how the battery energy, and PS parameter can be chosen to maximize the FU throughput while ensuring a desired NU throughput when there is imperfect interference cancellation at the NU. Computer simulation results validate the accuracy of the derived expressions, and demonstrate that augmenting the harvested energy with a small quantum of the relay's battery energy can considerably improve the FU performance. [ABSTRACT FROM AUTHOR]

In this paper, we present a civil aircrafts augmented space-air-ground integrated networks (CAA-SAGIN) architecture, where each mobile user can access multiple platforms simultaneously. With the target of ensuring fairness, we put forward the fair optimization strategies including resource allocation and resource auction. In the resource allocation, we formulate a service-oriented fair (SOF) resource allocation problem in order to minimize the difference between the allocated and required data rate. After introducing convex-relaxation and logarithmic approximation, the joint optimal solutions of subchannel and power allocation can be obtained by SOF iteration algorithm. Aiming at managing the terrestrial network overload, we present a user update mechanism. After applying SOF resource allocation for selected original users in sky access platforms, we propose a resource auction scheme so as to maximize the utility for both sides. First, we decompose the original problem into several subproblems and transform them into their lower bound by first-order approximation. Then, we can obtain the joint optimal solution with an alternating descent iterative method. From simulation results, we can find that CAA-SAGIN can bring great benefits to traditional terrestrial networks. In addition, the proposed resource allocation and auction schemes are significant in terms of telecommunication and economic parameters. [ABSTRACT FROM AUTHOR]

To be differentiated from the literature, in this paper, we aim to alleviate the impact of pilot contamination (PC) on the massive MIMO systems by cooperatively scheduling users (rather than just assigning) among neighboring cells to share the limited orthogonal pilots. To this end, we develop the multi-cell cooperative scheduling (MCCS) algorithm together with the cooperative scheduling indexes (COSIs) for maximizing the data rate, maximizing the Jain's fairness index and reaching a better tradeoff in-between. For convenience, they are denoted by the COSIs for the CMDR, CMMF and CPF schedulers, respectively. However, its high computational complexity may somehow resists its from practical applications. Thus, a low-complexity cooperative proportional fairness (LC-CPF) algorithm is designed to well approach the MCCS algorithm using the CPF COSI; and at the meantime, the order of computational complexity can be significantly reduced. Moreover, its ability to reach a better tradeoff can still be maintained under the impact of high spectrum-sharing interference. In addition, it is interesting to find that using the proposed cooperative scheduling methods, the open-loop power control mechanism is no longer required for compensating the differences of received signal quality between users. [ABSTRACT FROM AUTHOR]

This paper investigates the possibility of co-channel secondary transmission over the operational digital terrestrial video (DTV) broadcast bands within the interference limits of the DTV receivers. Aided by emulated DTV transmission experiments, secondary transmission-caused interference to the DTV receiver is analyzed. Using this understanding of interference behavior, a new transmission scheme for the secondary network nodes is proposed. The scheme selects the best communication parameters in terms of transmit power, spectral overlap, temporal occupancy, symbol duration, and modulation scheme to achieve a desired quality of service target within the interference limits of the DTV receivers. This is achieved without having information about the presence of DTV receivers. The feasibility as well as limits of the proposed secondary deployment scheme are then analyzed. This study is expected to serve as a valuable planning tool in deploying cognitive secondary networks over DTV transmission bands. [ABSTRACT FROM AUTHOR]

In a frequency division complementary coded CDMA (FD-CC-CDMA) system, multiple tuners have to be used for multi-carrier modulation, which has a very high complexity and power consumption. In this paper, we propose a CP-free OFDM scheme to implement multi-carrier modulation in an FD-CC-CDMA system, which is named as CP-free OFDM-CC-CDMA system. The transmitter in the CP-free OFDM-CC-CDMA system offers a unique flexibility to adjust the amount of data processed at the same time to ensure that the OFDM block size exceeds the delay spread of a multipath channel, which attributes to effective mitigation of multipath induced inter-symbol interference (ISI). At the receiver of a CP-free OFDM-CC-CDMA system, minimum mean square error (MMSE) equalization and MMSE combining are used to mitigate multi-user interference (MUI) and inter-carrier interference (ICI). The obtained results show that a CP-free OFDM-CC-CDMA system offers a much higher transmission efficiency than FD-CC-CDMA and OFDM-DS-CDMA systems. In addition, the proposed CP-free OFDM-CC-CDMA system outperforms OFDM-DS-CDMA system in terms of bit error rate due to its inherent powerful diversity gain. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of utility maximization in the uplink of vehicle-to-infrastructure communication systems. The studied scenarios consider four practical aspects of mobile radio communication links: i) Interference between adjacent channels, ii) interference between roadside units along the way, iii) fast and slow channel fadings, and iv) Doppler shift effects. We present first the system model for the IEEE 802.11p standard, which considers a communication network between vehicles and roadside infrastructure. Next, we formulate the problem of utility maximization in the network, and propose a distributed optimization scheme. This distributed scheme is based on a two-loop feedback configuration, where an outer-loop establishes the optimal signal to interference-noise ratio (SINR) that maximizes the utility function per vehicle and defines a quality-of-service objective. Meanwhile, inner-control loops adjust the transmission power to achieve this optimal SINR reference in each vehicle node regardless of interference, time-varying channel profiles and network latency. The computation complexity of the distributed utility maximization scheme is analyzed for each feedback loop. Simulation results indicate that the proposed scheme reaches the objective SINRs that maximize utility and improve energy efficiency in the network with a low time cost. The results also show that the maximum utility is consistently achieved for different propagation scenarios inside the vehicular communication network. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) has been widely considered as a promising technology in the next generation wireless communication systems. Various beam-based directional transmission techniques have been proposed to compensate high pathloss caused by mmWave properties. However, mobility effect of users potentially causes severe inter-beam interferences, which has not been fully-investigated in existing studies. In this paper, we have analyzed different types of mobility-aware beam interference models. Additionally, the theoretical SINR is derived based on channel statistics and the trajectories of users. We propose a mobility-aware subband and beam resource allocation (MSBA) scheme for the mmWave subband-beam massive multi-input multi-output (SB-MMIMO) systems. The proposed MSBA benefits from reduced computation complexity for maximizing system throughput constrained by quality-of-service (QoS) demands of users. The first phase of MSBA scheme is responsible for resource block assignment; while the second phase allocates beamwidth and beam directions according to the analytical derivations. Numerical results show that the proposed MSBA scheme can effectively achieve the highest system throughput and the lowest complexity compared to existing schemes in open literatures. [ABSTRACT FROM AUTHOR]

This correspondence paper studies the impact of nonidentically distributed channel estimation error on performance of a scheduled space-time block coding with mean-value power allocation in cognitive-radio multiple-input multiple-output system. Using the derived probability density function, the exact closed-form expressions of the proposed system for outage probability, ergodic capacity, and symbol-error rate (SER) with both $\rm M$ -ary quadrature amplitude modulation and phase shift keying modulation are derived. Using asymptotic analysis, this paper quantifies the diversity order for both outage probability and SER in the presence of nonidentically distributed error. From the analysis results, this paper shows that the diversity order is enhanced by the multiuser diversity as the number of user terminals increases regardless of outage probability and SER, while the spatial diversity is eliminated. [ABSTRACT FROM AUTHOR]

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]

Considering that the future cellular networks are more content-centric and content sharing among user equipments is more universal, device-to-device (D2D) technique attracts attention on supplying a feasible way for content delivery among proximal users without deploying additional infrastructure. Whereas some problems are still not clear such as the limitation on D2D communication for content delivery and which transmission mode (unicast or multicast) is more efficient. In this paper, the performance of content delivery is analyzed for D2D unicast and multicast, respectively. Several metrics such as the number of caching users, the number of request users, and the serving time of a content request are quantified with the consideration of user deployment and interference environment. These analyses provide an insight into D2D content delivery and deep understanding of D2D unicast and multicast on content delivery. To further distinguish appropriate conditions of employing unicast and multicast, energy efficiency is also investigated for two transmission modes. Extensive evaluations show that a better transmission mode can be selected based on the work presented in this paper. It is also verified that the efficiency of content delivery in cellular networks can be improved by this mode selection. [ABSTRACT FROM PUBLISHER]

Mobile services like GSM and LTE are increasingly offered on board of long-haul flights. This is achieved by installing an onboard base station, namely a GSM BTS or an LTE eNodeB in the airplane. Additionally, the airplane is equipped with a network control unit (NCU) device which prevents onboard mobile users from attempting to connect to ground mobile networks and, therefore, affect or interfere with terrestrial communications. The objective of this paper is to evaluate the need of the network control unit. For that purpose, it is investigated if a mobile user in the airplane can establish a connection with an existing terrestrial GSM or LTE network without the presence of the network control unit and the onboard base station. Only a few studies exist which investigate this connection. The analysis done in this paper takes into consideration physical and high layer requirements of both GSM and LTE networks. [ABSTRACT FROM PUBLISHER]

The next generation of mobile communication has progressed toward the deployment of small cells to meet the growing demands of increased capacity and QoS as compared to the conventional method, where all the computations were performed by the base station (BS)'s only. To reduce burden at the BS side, small cells deployment has been stressed upon, thus resulting in the formation of ultradense networks (UDN) having high concentration of small cells (e.g., picocell, femtocell, hotspots) and as a counter effect of which distance between two small cells is reduced to a greater extent. With such a close association of cells in UDN, the probability of frequent handovers also increases abruptly. As a result, the chances for attacker to spoof the bandwidth also increases many folds. In this paper, we have analyzed SNR, signal-to-interference-plus-noise ratio, and channel quality information channel parameters, such that the position of moving users at which handover is initiated in picocell deployment of UDN can be traced out successfully or region where the probability of attackers presence is high. Through this paper, we have tried to introduce the attacking scenario for the high mobility conditions in UDN. [ABSTRACT FROM AUTHOR]

The main focus of this paper is on multistream multiantenna (multiple-input multiple-output) communications in large-scale heterogeneous random networks. Previous work in this area mainly studies the outage probability from the perspective of a given stream, which is inaccurate as it generally overlooks possible interference-driven cross stream signal-to-interference correlation in each communication link. To tackle this issue, in this paper, we focus on a link-level performance evaluation by characterizing the complementary cumulative distribution function (CCDF) of random mutual information (RMI) under heterogeneous interference. We focus on the scenarios that no coordination among transmitters is persuaded, and the receivers do not attempt to cancel out part of interuser interference. Assume that channel state information is known at both the transmitter and receiver of each communication pair, Rayleigh fading, that the singular value decomposition (SVD) is applied to construct pre-coding/post-coding filters for single-user detection, and that transmitted signals of antennas are i.i.d. Gaussian. We first provide accurate expression for the achievable data rate (ADR) of each link, and show that, regardless of the interference power, when transceivers are equipped with equal number of antennas it grows sublinearly with the number of antennas. We then approximate RMI via Gaussian distribution that its mean is the ADR and its variance is derived based on network's parameters. It is seen that the Gaussian approximation is credible even when two streams of data are transmitted. This paper provides various insights regarding the impact of system parameters, including density of transmitters, path-loss exponent, and the number of antennas, on the ADR and CCDF of RMI. We finally spot tremendous benefits of the SVD scheme over other prominent multiplexing systems, including maximum ratio combining, zero-forcing, and diagonal BLAST superstructure with minimum mean square error receivers. [ABSTRACT FROM PUBLISHER]

Vector perturbation (VP) is a nonlinear precoding technique that achieves near-capacity performance in multiuser multiple-input multiple-output systems at the expense of large complexity due to the search for the optimum perturbation vector. In this paper, we present the hybrid Tomlinson–Harashima VP (TH-VP) algorithm, a novel zero-forcing precoding scheme, which combines TH precoding to remove interuser interference, and VP precoding to equalize each user's multiple spatial streams. We show that the two nonlinear techniques can be integrated in a single optimization and that the proposed algorithm has lower computational requirements than any other. The performance of TH-VP is analyzed and simulation results show that TH-VP outperforms conventional zero-forcing VP and approaches the performance of dirty paper coding. [ABSTRACT FROM AUTHOR]

This paper considers multicell scheduling for coordinated multiple-input multiple-output cellular networks. In a multicell scenario, intercell interference, which is the major challenge degrading system performance, can be suppressed via multicell coordination. However, when the number of users is larger than that can be served, user/multimode selection is necessary, and can significantly enhance the performance in such interference-limited environment. Nevertheless, user selection in a multicell scenario incurs high computational complexity and overhead signalling. To this end, in this paper, low complexity greedy algorithms are proposed for user selection. The algorithms are based on the concept of angle between subspaces and intersection of null spaces, and work in partially distributed fashion with limited information exchange. By these algorithms, channel feedback can be greatly reduced with reasonable computational complexity. In addition, multimode scheduling schemes are proposed for this multicell set up, where the spatial streams are adaptively selected. The proposed algorithms are analysed and compared with the optimal solution obtained by exhaustive search. Simulation results show that the algorithms achieve most of the throughput achievable by the optimal solution. [ABSTRACT FROM AUTHOR]

Very recent studies showed that in a fully loaded dense small cell network (SCN), the coverage probability performance will continuously decrease with the network densification. Such new results were captured in IEEE ComSoc Technology News with an alarming title of “Will Densification Be the Death of 5G?” In this paper, we revisit this issue from more practical views of realistic network deployment, such as a finite number of active base stations (BSs) and user equipments (UEs), a decreasing BS transmission power with the network densification, etc. Particularly, in dense SCNs, due to an oversupply of BSs with respect to UEs, a large number of BSs can be put into idle modes without signal transmission, if there is no active UE within their coverage areas. Setting those BSs into idle modes mitigates unnecessary intercell interference and reduces energy consumption. In this paper, we investigate the performance impact of such BS idle mode capability (IMC) on dense SCNs. Different from existing work, we consider a realistic path loss model incorporating both line-of-sight (LoS) and non-LoS transmissions. Moreover, we obtain analytical results for the coverage probability, the area spectral efficiency and the energy efficiency (EE) performance for SCNs with the BS IMC and show that the performance impact of the IMC on dense SCNs is significant. As the BS density surpasses the UE density in dense SCNs, the coverage probability will continuously increase toward one, addressing previous concerns on “the death of 5G”. Finally, the performance improvement in terms of the EE performance is also investigated for dense SCNs using practical energy models developed in the Green-Touch project. [ABSTRACT FROM PUBLISHER]

Both caching and interference alignment (IA) are promising techniques for next-generation wireless networks. Nevertheless, most of the existing works on cache-enabled IA wireless networks assume that the channel is invariant, which is unrealistic considering the time-varying nature of practical wireless environments. In this paper, we consider realistic time-varying channels. Specifically, the channel is formulated as a finite-state Markov channel (FSMC). The complexity of the system is very high when we consider realistic FSMC models. Therefore, in this paper, we propose a novel deep reinforcement learning approach, which is an advanced reinforcement learning algorithm that uses a deep $Q$ network to approximate the $Q$ value-action function. We use Google TensorFlow to implement deep reinforcement learning in this paper to obtain the optimal IA user selection policy in cache-enabled opportunistic IA wireless networks. Simulation results are presented to show that the performance of cache-enabled opportunistic IA networks in terms of the network's sum rate and energy efficiency can be significantly improved by using the proposed approach. [ABSTRACT FROM PUBLISHER]

Device-to-device (D2D) communication is developed as a new paradigm to enhance network performance according to LTE and WiMAX advanced standards. The D2D communication may have dedicated spectrum (overlay) or shared spectrum (underlay). However, the allocated dedicated spectrum may not be effectively used in the overlay mode, while interference between the D2D users and cellular users cause impairments in the underlay mode. Can the resource allocation of a D2D system be optimized using the cognitive approach where the D2D users opportunistically access the underutilized radio spectrum? That is the focus of this paper. In this paper, the transmission rate of the D2D users is optimized while simultaneously satisfying five sets of constraints related to power, interference, and data rate, modeling D2D users as cognitive secondary users. Furthermore, a two-stage approach is considered to allocate the radio resources efficiently. A new adaptive subcarrier allocation scheme is designed first, and then, a novel power allocation scheme is developed utilizing geometric water-filling approach that provides optimal solution with low computation complexity for this nonlinear problem. Numerical results show that the proposed approach achieved significant performance enhancement than the existing schemes. [ABSTRACT FROM PUBLISHER]

The level crossing rate (LCR) is an important second-order statistical quantity that characterizes the rate of occurrence of fading time intervals. In this paper, we investigate the LCR of multiantenna flat-fading channels in the presence of additive white Gaussian noise and cochannel interferers with unequal received powers and Doppler shifts. We first present a unified approach to derive the exact LCR of the signal-to-interference-noise ratio at a receiver, where maximum ratio combining is deployed over spatially correlated or uncorrelated systems. Through the exact LCR derivation, we identify an accurate approach to obtain a simplified approximate LCR expression in the spatially uncorrelated system case. Benefits of the LCR expressions derived in the paper are demonstrated in two important applications: 1) the packet error rate is evaluated through the finite-state Markov channel model; and 2) the optimum packet length to maximize the throughput of the system with the stop-and-wait automatic repeat request protocol is derived. The analytical results are validated by simulations. [ABSTRACT FROM PUBLISHER]

In cognitive radio (CR) networks, cooperative spectrum sensing is utilized to improve the sensing performance to avoid potential interference to primary users (PUs) and increase spectrum access opportunities for secondary users (SUs). A cooperative spectrum sensing process is divided into three phases: individual sensing/detection, reporting/fusion, and data transmission. In the reporting phase, one or more reporting channels are needed to transmit individual sensing results to a fusion center (FC), and global spectrum sensing results are determined at the FC. The number of required reporting channels depends on the number of spectrum sensors or SUs, which relates to reporting channel efficiency and channel scheduling complexity. That is to say, the reporting channel design can be a challenge, especially when fixed assignment scheduling is used. Therefore, in this paper, we design a reporting channel scheme based on random access protocols, including slotted Aloha and reservation-Aloha. Performance evaluations in terms of PU detection probabilities and false alarm probabilities considering the proposed reporting channels are presented. In addition, the impact of soft/unquantized spectrum sensors or detectors (SUs) and malicious SUs is considered in this paper. Analytical and simulation results illustrate the effectiveness of the proposed reporting channel scheduling methods in improving the cooperative spectrum sensing performance. [ABSTRACT FROM AUTHOR]

With the ever-growing number of mobile users and the rapid growth of wireless data service requirement, quality of experience (QoE) has emerged as an essential indicator for users, service providers, and operators. Meanwhile, to improve coverage and serve users, a lot of small cell base stations (SBSs) must be installed, and a great amount of energy is consumed. However, as far as is known, there are few works that have studied the combinatorial problem of QoE and energy aware SBS management, which jointly implements power selection, load management (SU allocation), and channel allocation. This paper investigates the problem of QoE and energy aware SBS management, which consists of power selection, load management, and channel allocation. In this paper, we resort to cloud technologies to solve such a complicated combinatorial problem and employ an iterative approach in which two subproblems are alternatively assigned and optimized at each iteration, i.e., 1) transmission power and load joint management and 2) channel allocation. We propose a two-dimensional-action extended weakly acyclic game theoretical scheme to optimize the two subproblems distributedly and iteratively. We define a novel two-dimensional-action pure strategy Nash equilibrium (2D-NE) and prove that at least one 2D-NE exists in the proposed game. With the help of cloud, we propose two kinds of better response algorithms to achieve 2D-NE of the proposed game $G_w$ . Moreover, simulation results show that the proposed approach could achieve a good QoE-energy utility performance and a high QoE energy efficiency. [ABSTRACT FROM AUTHOR]

Convergence and density evolution of a low-complexity iterative multiple-input multiple-output detection based on belief propagation over a ring-type pairwise graph are presented for binary data. The detection algorithm to be considered is effectively a forward–backward recursion and was originally proposed by Yoon and Chae in a work published in 2014, in which link-level performance, computational complexity, and convergence for Gaussian input were analyzed in detail. This paper presents the convergence proof and the density evolution framework for binary input to give an asymptotic performance in terms of average signal-to-interference-plus-noise ratio and bit error rate (BER) without channel coding. The BER curve obtained via density evolution shows a good match with the simulation results for uncoded BER in the paper by Yoon and Chae verifying the effectiveness of the analysis provided and the performance of the detection algorithm. [ABSTRACT FROM AUTHOR]

Recent studies show that the statistical channel state information (SCSI) helps to largely increase the capacity of communication systems when the instantaneous perfect CSI is unavailable. In this paper, we consider multiuser multiple-input-single-output broadcast channels where the transmitter has the knowledge of SCSI. The major issue of concern in our paper is to improve the average group-rate of the whole system by scheduling users over different time slots. With SCSI at the transmitter side, we are able to precode signals and, hence, compute the theoretical achievable group-rate of arbitrary user groups. Based on the group-rates, we propose tier-2 Munkres user scheduling algorithm (T2-MUSA) that leads to higher average group-rate than existing algorithms with generally better fairness. The optimality of the proposed algorithm in energy-fair user scheduling space is proved and we derive a lower bound of a special case to verify the validity of our simulations. In addition, many conventional user scheduling algorithms maintain queue stability by solving a weighted sum-rate (WSR) problem, using queue lengths to represent weight coefficients. Inspired by T2-MUSA, we propose a QoS-based MUSA (QB-MUSA) aimed at stabilizing queue lengths and maximizing throughput. In results, we show that QB-MUSA exhibits higher throughput than the conventional WSR-based algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose a green spectrum and infrastructure leasing framework for sharing unused TV spectrum, in which the ownership of the network infrastructure and spectrum are decoupled, and each can be leased as a service on demand. An incumbent TV spectrum owner (TSO) can lease a share of the infrastructure from a network infrastructure owner (NIO) with a pay-per-use model, to provide new services to its end users. On the other hand, a TSO can rent a portion of its unused spectrum to the NIO for revenue such that the NIO can obtain access to the spectrum to serve its customers. This proposed framework achieves green communications through both resource sharing and energy saving. Our paper aims to analyze the interplay between TSO and NIO, and create a win–win situation to provide sufficient incentives for them to cooperate on this green communications. A multistage Stackelberg game is formulated, where TSO and NIO sequentially determine the total bandwidth supply for sharing, the infrastructure leasing price, the amount of infrastructure to lease, the spectrum leasing price, and the amount of spectrum to lease to maximize their utilities. The best strategies that will be taken by the TSO and NIO under various deployment scenarios are analyzed. Evaluation results show that the proposed green spectrum and infrastructure leasing framework is a promising scheme under which both TSO and NIO can benefit, and their utilities can be maximized in terms of user data throughput and revenue/payment, which provides sufficient incentives for them to cooperate. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of energy efficiency in cellular heterogeneous networks (HetNets) is investigated using radio resource and power management combined with the base station (BS) ON/OFF switching. The objective is to minimize the total power consumption of the network while satisfying the quality of service requirements of each connected user. We consider the case of coexisting macrocell BS, small cell BSs, and private femtocell access points (FAPs). Three different network scenarios are investigated, depending on the status of the FAPs, i.e., HetNets without FAPs, HetNets with closed FAPs, and HetNets with semiclosed FAPs. A unified framework is proposed to simultaneously allocate spectrum resources to users in an energy efficient manner and switch OFF redundant small cell BSs. The high complexity dual decomposition technique is employed to achieve optimal solutions for the problem. A low complexity iterative algorithm is also proposed and its performances are compared to those of the optimal technique. The particularly interesting case of semiclosed FAPs, in which the FAPs accept to serve external users, achieves the highest energy efficiency due to increased degrees of freedom. In this paper, a cooperation scheme between FAPs and mobile operator is also investigated. The incentives for FAPs, e.g., renewable energy sharing and roaming prices, enabling cooperation are discussed to be considered as a useful guideline for interoperator agreements. [ABSTRACT FROM PUBLISHER]

In traditional orthogonal frequency division multiplexing (OFDM) systems, a cyclic prefix (CP) must be used in every block for intersymbol interference (ISI) suppression in time-dispersive channels at a price of severely impaired spectrum efficiency. To deal with this issue, the symbol cyclic shift equalization (SCSE) algorithm was proposed to implement a CP-free OFDM system. In this paper, we aim to further reduce the computational complexity of the SCSE algorithm. In particular, a pulse amplitude modulation (PAM) is used at a transmitter to construct conjugate symmetric OFDM blocks, while only partial samples in an OFDM block are involved in the SCSE algorithm at the receiver side, leading to a significantly reduced implementation complexity if compared to an SCSE quadratic-amplitude modulation(QAM)/phase-shift keying (PSK)-OFDM system, where all samples in an OFDM block must be involved in the detection process. The performance of the proposed SCSE PAM-OFDM scheme is analyzed and compared to traditional OFDM systems. The results obtained from this paper verify the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a heterogenous network in which low-power indoor femtocells are deployed in the coverage area of the existing macrobase station (MBS). This paper proposes a novel coordinated random beamforming and user-scheduling strategy to improve the throughput of users served by the femtocell access point (FAP) while satisfying the quality-of-service (QoS) requirements of users served by both MBS and FAP. The strategy, termed as QoS-aware coordinated scheduling (QACS), requires limited coordination between the MBS and FAP, i.e., only the indexes of the qualified beams are shared. Exact statistical analysis for the ergodic achievable rate of both FAP and MBS with the proposed strategy are presented. Scheduling fairness is also addressed for the proposed QACS. [ABSTRACT FROM PUBLISHER]

Non-orthogonal multiple access (NOMA) aided unmanned aerial vehicle (UAV) is becoming a promising technique for future wireless networks. However, its security remains a great challenge due to the line-of-sight in UAV communications and high transmit power for weak users in NOMA. Thus, in this paper, we propose a power allocation (PA) scheme for NOMA-UAV networks with circular trajectory, to maximize the sum rate of common users while guaranteeing the security for a specific user. To achieve this, we consider three cases based on the distance from the UAV to the secure user. Specifically, the lowest transmit power is assigned to the secure user in each time slot to guarantee its security, with the remaining power allocated to common users to maximize their sum rate. Due to the non-convexity of the problem, we analyze its monotonicity and derive the closed-form solutions for these three cases. To further improve the transmission rate of the secure user, we also derive the upper bound for its decoding threshold, and analyze the linear relationship between the secure decoding threshold and the sum rate of common users. Simulation results are demonstrated to evaluate the effectiveness of the proposed secure PA scheme in NOMA-UAV networks. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has been deemed a promising technology to achieve high spectral efficiency. This paper investigates transmit power optimization for a multi-user multiple-input single-output (MISO) NOMA downlink system endowed with energy harvesting and physical layer security. More specifically, the system is designed to satisfy the data-link security requirements of its legitimate users while charging energy harvesting devices. To achieve that goal, we investigate a joint design on beamforming vectors and artificial noise (AN) covariance matrix. Then, an iterative difference-of-two-convex-function (D.C.) algorithm is proposed by applying the successive convex approximation (SCA) approach. To further reduce the computational complexity, a sub-optimal alternating D.C. (ADC) algorithm is devised by decoupling beamforming and mapping the AN to the null space of legitimate users. In the ADC algorithm, optimal null space and beamforming vectors are alternately solved by convex programming. Furthermore, the convergence of the proposed D.C. and ADC algorithms is derived. Extensive simulation results show that the two proposed AN-aided algorithms significantly reduce the transmit power cost over OMA and NOMA scheme without AN, especially when there are more eavesdroppers. [ABSTRACT FROM AUTHOR]

This paper proposes a pulse compression method by using the offset quadrature amplitude modulation based orthogonal frequency division multiplexing (OQAM-OFDM) signal without inserting any cyclic prefix (CP). A modified interference approximation-based pulse compression method (MIA-based PCM) is proposed, by exploiting the demodulated real weights of the OQAM-OFDM signal, the inter-symbol and inter-subcarrier interferences to enhance the performance. The MIA-based PCM achieves approximated inter-range-cell interference (IRCI)-free pulse compression and perfect Doppler estimation, which has both the benefits of power efficiency and good Doppler tolerance. Finally, numerical simulation results are provided and discussed. [ABSTRACT FROM AUTHOR]

Wireless channels generally exhibit dispersion in both time and frequency domain, known as doubly selective or doubly dispersive channels. To combat the delay spread effect, multicarrier modulation (MCM) such as orthogonal frequency division multiplexing (OFDM) and its universal filtered variant (UF-OFDM) can be employed, leading to a simple per-subcarrier one tap equalization. The time-varying nature of the channel, in particular, the intra-multicarrier-symbol channel variation induces spectral broadening and thus inter-carrier interference (ICI). Most existing works address both effects separately, focusing on the one effect while ignoring the respective other. This paper considers both effects simultaneously for cyclic prefix (CP)-, zero padded (ZP)- and universal filtered (UF)-based OFDM with a simple one tap equalization, assuming doubly dispersive wireless channel model. For this general channel model, we show that the independent (wide sense stationary uncorrelated scatter, WSSUS) selectivity in time and frequency domain starts to intertwine in contrast to the ideal cases with single selectivity. We derive signal-to-interference-plus-noise ratio (SINR) in closed form for arbitrary system settings and channel parameters, e.g., bandwidth, delay- and Doppler-spread. With the SINR analysis, we compare the three MCM schemes under different channel scenarios. [ABSTRACT FROM AUTHOR]

To meet the exponentially increasing air traffic, L-band (960--1164 MHz) digital aeronautical communication system (LDACS) has been introduced. The LDACS aims to exploit the vacant spectrum between incumbent Distance Measuring Equipment (DME) signals and envisioned to follow an orthogonal frequency division multiplexing (OFDM) approach to support high-speed delay-sensitive multimedia services. This paper deals with the design and implementation of end-to-end LDACS the transceiver on the Zynq System on Chip platform, consisting of FPGA as programmable logic (PL) and ARM as processing system (PS). We consider OFDM based LDACS and improve it further using windowing and/or filtering. We propose a hardware-software co-design approach and analyze various transceiver configurations by dividing it into PL and PS. We demonstrate the flexibility offered by such a co-design approach to choose the configuration as well as word-length for a given area, delay and power constraints. The transceiver is also integrated with the programmable analog front-end to validate its functionality in the presence of various RF impairments and wireless channels and interference specific to the LDACS environment. Via in-depth performance analysis concerning parameters such as out-of-band attenuation, DME interference, bit-error-rate, word-length, and complexity, we demonstrate wide bandwidth filtered OFDM as an attractive solution for the next generation LDACS. [ABSTRACT FROM AUTHOR]

Incipient fault detection and diagnosis (FDD) is an important measure to improve the efficient, safe and stable operation of high-speed trains. This paper proposes a data-driven FDD method, namely deep slow feature analysis and belief rule base method (DSFA-BRB), for the running gears of high-speed trains. The method uses two kinds of statistics to perform fault detection on the multi-dimensional data of the running gears. In addition, the characteristics of more accurate data are extracted, which greatly reduces the complexity of constructing a diagnostic and quantitative model. Further, by constructing a BRB model combining expert knowledge and data, it is possible to avoid misjudgment caused by data incompleteness. Compared with the traditional methods, the DSFA-BRB algorithm has better performance in reducing fault alarm probability. Finally, the validity of the algorithm is verified by the actual running gears system. [ABSTRACT FROM AUTHOR]

This paper aims at investigating the tradeoff between ergodic energy efficiency (EE) and spectral efficiency (SE) for device-to-device (D2D) communications underlaying cellular networks. Assuming average-based resource allocation, we propose a multiobjective optimization problem (MOOP) approach to deal with the EE and SE maximization problem. Specifically, the formulated MOOP results in the maximization of the total ergodic sum rate of the D2D users and the minimization of the total average transmit power of the D2D transmitters. Two practical scenarios are considered, i.e., a limited interference scenario, which includes the sparsely deployed scenario, and a densely deployed scenario, where for each scenario the maximum achievable EE and SE are derived. Specifically, considering the limited interference scenario, an upper bound is imposed on the received interference across different D2D communications, and closed-form expressions for the optimal power allocation, ergodic sum rate, and maximum EE are obtained. In the general, densely deployed scenario, however, the cross D2D network interference needs to be taken into account. We provide an optimal solution for the power control based on sequential fractional programming to tradeoff between complexity and performance gain. Simulation results unveil an interesting tradeoff to strike a balance between EE and SE. [ABSTRACT FROM AUTHOR]

Interference is one of the most critical issues in the device-to-device (D2D)-enabled heterogeneous cellular networks (HetCNets) due to the coexistence of D2D pairs and various types of cellular user equipments (UEs) that operate in the same spectrum. In this paper, an interference management scheme of joint mode selection and power control is proposed to solve the issue in D2D-enabled HetCNets. In the scheme, we present power control with interference limited area (PC-ILA) in which power control is utilized to adjust the ILA dynamically. Furthermore, according to different ILA, users can select different communication modes to solve the problem of spectrum resource waste caused by a single communication mode. Numerical simulation results are provided to demonstrate the feasibility of the proposed scheme and its superiority over other schemes. Moreover, the proposed mode selection method achieves superior performance compared with existing well-known methods. [ABSTRACT FROM AUTHOR]

Current cellular systems use pilot-aided statistical-channel state information (S-CSI) estimation and limited feedback schemes to aid in link adaptation and scheduling decisions. However, in the presence of pulsed radar signals, pilot-aided S-CSI is inaccurate since interference statistics on pilot and non-pilot resources can be different. Moreover, the channel will be bimodal as a result of the periodic interference. In this paper, we propose a max-min heuristic to estimate the post-equalizer SINR in the case of non-pilot pulsed radar interference, and characterize its distribution as a function of noise variance and interference power. We observe that the proposed heuristic incurs low computational complexity, and is robust beyond a certain SINR threshold for different modulation schemes, especially for QPSK. This enables us to develop a comprehensive semi-blind framework to estimate the wideband SINR metric that is commonly used for S-CSI quantization in 3GPP Long-Term Evolution (LTE) and New Radio (NR) networks. Finally, we propose dual CSI feedback for practical radar-cellular spectrum sharing, to enable accurate CSI acquisition in the bimodal channel. We demonstrate significant improvements in throughput, block error rate and retransmission-induced latency for LTE-Advanced Pro when compared to conventional pilot-aided S-CSI estimation and limited feedback schemes. [ABSTRACT FROM AUTHOR]

In this paper, a full-duplex unmanned aerial vehicle-(UAV) base station is used to provide wireless communication to an area lacking a conventional terrestrial infrastructure, and its efficient deployment is investigated. More concretely, the UAV positioning and resource allocation problems are solved with the aim of minimizing the transmit power of the UAV, while serving users with their rate requirements and accounting for the backhaul limitation of the UAV. To this end, a complete solution for the optimal 3D position of the UAV, the bandwidth assignment and the transmit power distribution in the access and backhaul links is proposed that accounts for both the backhaul interference and the self-interference. When the UAV power budget is insufficient to fulfill rate requirements, non-orthogonal multiple access (NOMA) pairing is conducted to enhance system performance. Simulation results show that, when using the proposed approach, both the achieved sum rate and the percentage of satisfied users are significantly increased, when compared to a strategy that uses separate frequency bands in the access and backhaul links, as well as to a previously proposed method. [ABSTRACT FROM AUTHOR]

User-centric ultra-dense network (UDN) has been considered a key enabler of high data rate and high reliable vehicle-to-infrastructure (V2I) communication. In this paper, an analytical framework is developed based on stochastic geometry to characterize the uplink V2I transmission performances, in terms of the outage probability, the average vehicle throughput and the average spatial throughput, particularly resolving two important but not well-understood factors in such networks: the spatial correlation in the interference powers among the cooperative roadside units (RSUs) as caused by the shared set of co-channel vehicles, and the combined vertical distance (CVD) owing to the lane width and the antenna height difference between the vehicle and the RSUs. Exact analytical expressions of the outage probability are derived for the general multiple association cases, a far-distance approximation method is introduced to reduce the computational complexity, and lower and upper bounds are obtained corresponding to two extreme assumptions of the spatial interference correlation. We show that the impacts of the spatial interference correlation can be significant and ignoring the correlation can lead to non-optimal system deployment, and that the far-distance approximation can approach well with the exact results. Meanwhile, although CVD diminishes the V2I uplink transmission performances, the diminution can be mitigated through RSU cooperation. [ABSTRACT FROM AUTHOR]

Backscattering assisted wireless-powered communication combines ultralow-power backscatter transmitters with energy harvesting devices. This paper investigates the transmission mode selection problem of a hybrid relay that forwards data by switching between the active wireless-powered transmission and the passive ambient backscattering. It first presents a hybrid relay system model and derives its end-to-end success probability under theoretically optimal, but practically unrealistic, conditions. The transmission mode selection is then formulated as a stochastic two-armed bandit problem in a varying environment where the distributions of rewards are nonstationary. The proposed model selection scheme does not assume to have access to any channel states or network conditions, but merely relies on learning from past transmission records. Numerical analyses are performed to validate the proposed bandit-based mode selection approach. [ABSTRACT FROM AUTHOR]

Zero-forcing precoding is a commonly-used multiple-user, multiple-input multiple-output beamforming technique. Applying such precoding, the signal-to-interference-plus-noise ratio (SINR) statistics with outdated channel state information, which involve various projections related to the multi-dimensional channel vectors and precoding vectors, have never been explicitly derived. In this paper, for the multiple-input single-output scenario with uniform power allocation, the distributions of these projections are derived, and then the SINR distribution and the conditional outage probability can be computed using those distributions. [ABSTRACT FROM AUTHOR]

This paper conducts the performance analysis of a hybrid satellite-terrestrial cooperative network (HSTCN) having multi-antenna terrestrial relays. By assuming the availability of the direct link between the satellite and the destination, and considering the effects of hardware impairments (HIs) and interference on both relays and destination, we first propose a relay selection scheme to enhance the quality of the downlink transmission of the considered HSTCN. Then, we derive analytical expressions for the outage probability (OP) and throughput of the system using the proposed relay selection scheme. Furthermore, the asymptotic behavior of the HSTCN at high signal-to-noise-ratio (SNR) is also investigated to reveal the diversity order and array gain of the system. Finally, computer simulation results are provided to show the effectiveness of the relay selection scheme. The analysis shows that the system performance is significantly affected by the HIs and interference. [ABSTRACT FROM AUTHOR]

In this paper, we propose a system model for cellular vehicle-to-everything (C-V2X) networks mode-3, with two user groups: cellular users and vehicular users. Cellular users communicate with each other through the base station (BS). Vehicular users communicate through direct vehicular links while sharing the spectrum of an orthogonal frequency division multiplexing (OFDM) system with cellular users. In particular, we focus on the underlay approach, in which vehicular users can transmit at the same time in a sub-carrier that is being used by a cellular user. Assuming a limited number of sub-carriers, the number of allowed vehicular links is limited by the quality of service (QoS) requirement for cellular users because of the interference from vehicular links. Our goal is to maximize the number of vehicular links while satisfying the QoS for cellular users. To achieve this goal, we state the optimization problem of resource allocation in C-V2X networks mode-3, assuming high mobility of vehicular users, which results in Doppler effect for them. We also assume that the global channel state information (CSI) of mobile links is not available for the BS. We propose a novel scheme for the BS to jointly allocate resources, such as power and sub-carriers, to cellular and vehicular users, while minimizing the number of non-allowed vehicular links, considering high data rate requirements for cellular users and high reliability requirements for vehicular users. Using numerical results, we obtain the maximum number of vehicular links that can be established for a given available bandwidth and cellular user distribution. [ABSTRACT FROM AUTHOR]