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We investigate multiuser detection under uplink asynchronous scenario, where the triangular successive interference cancellation (T-SIC) detection scheme is exploited. As the existing analysis was conducted under some ideal assumptions for simplicity, the asynchronous scenario is analyzed under rigorous assumptions in this paper so that important insights are revealed for practical systems. Specifically, the average symbol error rate (SER) formulas are derived for a two-user system with arbitrary $M$ -ary quadrature amplitude modulation ($M$ -QAM) over Rayleigh fading channels. These solutions are shown to have higher accuracies compared to the existing solutions. Furthermore, a novel iterative detection algorithm is proposed, i.e., the parallel T-SIC method, which is more efficient and effective compared to the iterative T-SIC method. Insightful discussion is conducted in terms of the potentials of the concerned iterative detection method. Simulation results show that the most significant improvement of the iterative detection reflects on the SER for the strongest user, and the reduction is always within 50% of the SER compared to the primary detection. The gains obtained by the iterative detection is negligible for higher order $M$ -QAM cases. [ABSTRACT FROM AUTHOR]

Analysis on the exact error rate of jointly optimal (JO) maximum likelihood (ML) multiuser detection is limited in the existing literature owing to its high computational complexity. In this paper, the JO ML detection of two quadrature phase-shift keying (QPSK) signals with an arbitrary relative phase offset is investigated. Exact, analytical symbol error rate (SER) and bit error rate (BER) formulas are derived for two users with no less than 3 dB power difference between them. Closed-form union bounds on the user SER and BER with an arbitrary phase offset and an arbitrary user power ratio are also given as a simpler approach to acquire the asymptotic error rate performance. Furthermore, insights on the potentials and properties of the JO ML detector regarding its error rate behaviors for each user are revealed through comparisons with the successive interference cancellation receiver. The accuracies of the obtained formulas are demonstrated through simulation. The results show the error rates for the two-user QPSK case no longer follow the classic knowledge on the error rate behaviors in the single signal detection. In addition, the performance and dB penalty employing different modulation types are also compared and discussed. [ABSTRACT FROM AUTHOR]

This paper presents a novel and effective deep reinforcement learning (DRL)-based approach to addressing joint resource management (JRM) in a practical multi-carrier non-orthogonal multiple access (MC-NOMA) system, where hardware sensitivity and imperfect successive interference cancellation (SIC) are considered. We first formulate the JRM problem to maximize the weighted-sum system throughput. Then, the JRM problem is decoupled into two iterative subtasks: subcarrier assignment (SA, including user grouping) and power allocation (PA). Each subtask is a sequential decision process. Invoking a deep deterministic policy gradient algorithm, our proposed DRL-based JRM (DRL-JRM) approach jointly performs the two subtasks, where the optimization objective and constraints of the subtasks are addressed by a new joint reward and internal reward mechanism. A multi-agent structure and a convolutional neural network are adopted to reduce the complexity of the PA subtask. We also tailor the neural network structure for the stability and convergence of DRL-JRM. Corroborated by extensive experiments, the proposed DRL-JRM scheme is superior to existing alternatives in terms of system throughput and resistance to interference, especially in the presence of many users and strong inter-cell interference. DRL-JRM can flexibly meet individual service requirements of users. [ABSTRACT FROM AUTHOR]

Two-user non-orthogonal multiple access systems with quadrature phase-shift keying modulation are studied. A time asynchronous scheme for successive interference cancellation receivers that maximally suppresses the inter-user interference compared to any other time asynchronous schemes is proposed. Exact bit error rate (BER) solutions for the two users operating in the additive white Gaussian noise channel using the proposed scheme are derived. A simpler closed-form BER approximation for the weaker user is also presented. Compared to the symbol-synchronous scheme, numerical results show the proposed asynchronous scheme reduces the BER for the stronger signal by a factor of one-half. [ABSTRACT FROM AUTHOR]

Due to the complexity and associated inordinate computing time required to generate generalized Gaussian random variates, it is necessary to find faster ways to simulate events caused by additive generalized Gaussian noise. Following a concise review of the two known exact methods of generating generalized Gaussian random variates, an exact weighted counting approach is investigated for rapid estimation of the probability of events caused by the presence of additive generalized Gaussian noise. The weighted counting method reduces simulation times typically by 104 times, and will allow simulation of complex systems not previously feasible. [ABSTRACT FROM AUTHOR]

A full-duplex, amplify-and-forward multiple relay system employing simultaneous wireless information and power transfer receivers operating in interference channels is studied. Since all links want to maximize their own achievable rate, a power allocation problem under transmit power and energy harvesting constraints is developed. Through alternative optimization, a distributed iterative water-filling algorithm based on game theory with provable convergence is devised. The existence and uniqueness of a Nash equilibrium point are both guaranteed and the convergence of the proposed algorithm is examined using a diagonally strict concavity condition. Numerical results show that the proposed algorithm is convergent and can achieve a higher sum rate than previous schemes. [ABSTRACT FROM AUTHOR]

It is challenging to realize ultra-reliable and low latency communications (URLLC) under severe shadow fading and imperfect channel state information (CSI). However, reliability can be increased by exploiting space diversity from multiple receive antennas rather than retransmission with limited latency. Massive multi-user multiple-input-multiple-output (MU-MIMO) is studied to enable URLLC with imperfect CSI from least-square channel estimation. The linear minimum error probability (MEP) detector with a given length of pilots (LoP) is derived. Further, the LoP is optimized to minimize the error probability of the uplink with a limited number of channel uses, using the finite blocklength information theory and one-dimensional search methods. Numerical results verify that the proposed linear MEP detection incorporated in massive MU-MIMO improves reliability with limited latency and imperfect CSI. [ABSTRACT FROM AUTHOR]

Single-input multiple-output non-orthogonal multiple access (SIMO-NOMA) is a promising technology for the uplink (UL) of the Internet of things (IoT). A rate splitting scheme to guarantee max-min fairness (MMF) of SIMO-NOMA is studied. First, the achievable data rate of the minimum mean square error successive interference cancellation (MMSE-SIC) detection is formulated. An upper bound for the minimum data rate of UL users is derived, and it is proved that the upper bound can be achieved by rate splitting with MMSE-SIC detection. Then, an exhaustive-search rate splitting algorithm to maximize the minimum data rate is designed. The existence of a lower bound for the minimum data rate with two-layer SIMO-NOMA is proved. A low-complexity two-layer rate splitting algorithm is designed with suitable detection order to exceed the lower bound. Numerical results verify that rate splitting SIMO-NOMA has higher minimum data rate and lower transmission latency than single-input multiple-output orthogonal multiple access (SIMO-OMA) and un-layered SIMO-NOMA. [ABSTRACT FROM AUTHOR]

We develop the optimal economical caching schemes in cache-enabled heterogeneous networks, while delivering multimedia video services with personalized viewing qualities to mobile users. By applying scalable video coding (SVC), each video file to be requested is divided into one base layer (BL) and several enhancement layers (ELs). In order to assign different transmission tasks, the serving small-cell base stations (SBSs) are grouped into $K$ clusters. The SBSs are able to cache and cooperatively transmit BL and EL contents to the user. We analytically derive expressions for successful transmission probability and ergodic service rate, and then the closed-form expression for EConomical Efficiency (ECE) is obtained. In order to enhance the ECE performance, we formulate the ECE optimization problems for two cases. In the first case, with equal cache size equipped at each SBS, the layer caching indicator is determined. Since this problem is NP-hard, after the $l_{0}$ -norm approximation, the discrete optimization variables are relaxed to be continuous, and this relaxed problem is convex. Next, based on the optimal solution derived from the relaxed problem, we devise a greedy-strategy based heuristic algorithm to achieve the near-optimal layer caching indicators. In the second case, the cache size for each SBS, the layer size, and the layer caching indicator are jointly optimized. This problem is a mixed integer programming problem, which is more challenging. To effectively solve this problem, the original ECE maximization problem is divided into two subproblems. These two subproblems are iteratively solved until the original optimization problem is convergent. Numerical results verify the correctness of the theoretical derivations. Additionally, compared to the most popular layer placement strategy, the performance superiority of the proposed SVC-based caching schemes is testified. [ABSTRACT FROM AUTHOR]

Cooperative spectrum sensing based on the limiting eigenvalue ratio of the covariance matrix offers superior detection performance and overcomes the noise uncertainty problem. While an exact expression exists, it is complex and multiple useful approximate expressions have been published in the literature. An improved, more accurate, integral solution for the probability density function of the ratio is derived using order statistical analysis to remove the simplifying, but incorrect, independence assumption. Thereby, the letter makes an advance in the rigorous theory of eigenvalue-based spectrum sensing. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has been developed as a key multi-access technique for 5G. However, secure transmission remains a challenge in NOMA. Especially, the user with weakest channel is most threatened by eavesdropping, due to its highest transmit power. Two schemes are proposed to generate artificial jamming at the NOMA base station (BS), aiming at disrupting the potential eavesdropping without affecting the legitimate transmission. In the first scheme, the transmit power of artificial jamming is maximized, with its received power at each receiver higher than that of other users. Thus, the jamming signal can be eliminated via successive interference cancellation before others. When the transmit power of the BS is inadequate, the transmit jamming power is maximized with the jamming signal zero-forced at each receiver. Thus, the legitimate transmission is not affected by the jamming, and the eavesdropping can be disrupted effectively. Due to the non-convexity of these two optimization problems, we first convert them to convex ones and, then, provide an iterative algorithm to solve them. Simulation results are presented to show the effectiveness of the proposed schemes in guaranteeing the security of NOMA networks. [ABSTRACT FROM AUTHOR]

A multi-user multiple-input single-output simultaneous wireless information and power transfer full-duplex system with imperfect channel state information is considered. Under the assumption that the unknown channel estimation error is within a certain range, the self-interference cannot be suppressed completely at the base station and at the multi-user nodes. The proposed design problem is formulated as maximizing the average harvested energy of multi-user nodes and maintaining the signal-to-interference-plus-noise ratio requirement, which is proved to be non-convex. Utilizing semidefinite relaxation and S-procedure methods, a convex optimization problem of optimal beamforming vector for the multi-antenna transmitter is obtained. Moreover, semidefinite relaxation is proved to be tight by showing the existence of rank-one optimal solutions. Simulation results are presented to verify the robustness and effectiveness of the proposed algorithm compared with the non-robust design. [ABSTRACT FROM AUTHOR]

Fairness among different users and energy utilization are key issues in the future communication network design. Robust max–min fairness resource allocation in sensing-based wideband cognitive radio with simultaneous wireless information and power transfer is studied when spectrum sensing and channel state information are imperfect. A worst-case throughput is maximized by jointly optimizing the sensing time, transmit power, and subchannel allocation under the worst-case channel state information error model, subject to constraints on energy harvesting, interference power, and transmit power. Two operation paradigms for cognitive radio are considered, namely, opportunistic spectrum access and sensing-based spectrum sharing. The formulated robust max–min fairness resource allocation problems are mixed-integer and nonconvex programming with infinite inequality constraints. An efficient one-dimensional search algorithm is designed based on the proposed transmit power and subchannel allocation scheme. Simulation results show that the secondary user under sensing-based spectrum sharing can obtain a performance gain compared with that under opportunistic spectrum access at the cost of implementation complexity. Design tradeoffs are identified and discussed. [ABSTRACT FROM AUTHOR]

By suppressing repeated content deliveries, wireless caching has the potential to substantially improve the energy efficiency (EE) of the fifth-generation communication networks. In this paper, we propose two novel energy-efficient caching schemes in heterogeneous networks, namely, scalable video coding (SVC)-based fractional caching and SVC-based random caching, which can provide on-demand video services with different perceptual qualities. We derive the expressions for successful transmission probabilities and ergodic service rates. Based on the derivations and the established power consumption models, the EE maximization problems are formulated for the two proposed caching schemes. By taking logarithmic approximations of the $l_{0}$ -norm, the problems are efficiently solved by the standard gradient projection method. Numerical results validate the theoretical analysis and demonstrate the superiority of our proposed caching schemes, compared to three benchmark strategies. [ABSTRACT FROM AUTHOR]

The Beckmann distribution has a wide range of applications in radio-frequency communications, free-space optical (FSO) communications, and underwater wireless optical communications (UWOC). However, the cumulative distribution function (cdf) of the Beckmann random variable (RV) does not have a closed-form expression, which makes it challenging to derive analytical solutions for the outage probability of systems involving Beckmann RVs. In this paper, we study the generalized Beckmann distribution, which includes the Beckmann, Rayleigh, Rician, Nakagami- $m$ , Hoyt, $\kappa $ - $\mu $ , $\eta $ - $\mu $ , single-sided Gaussian, and the Beaulieu-Xie distributions as special cases. Three approaches are proposed to estimate the cdf of the generalized Beckmann distribution, including closed-form upper and lower cdf bounds, single-fold integration based on the closed-form characteristic function, and a left-tail cdf approximation. We compare the three approaches in terms of the ranges of applications and the computation time complexity. Based on the new cdf estimation techniques, one can efficiently evaluate the outage probabilities of pointing-error-limited FSO systems, UWOC systems, and maximum-ratio combining over arbitrarily correlated generalized Beckmann channels. [ABSTRACT FROM PUBLISHER]

The explosive growth of mobile data traffic and the scarcity of available licensed spectrum make resource allocation in heterogeneous networks a critical issue. A distributed resource allocation algorithm for software defined cellular networks for future 5G networks is proposed. The adoption of integrated femto-WiFi small cells is used to alleviate spectrum shortage, by permitting simultaneous access to both the licensed bands (via cellular interface) and unlicensed bands (via WiFi interface). A weighted utility maximization problem is formulated to optimize resource allocation, utilizing the software defined network controller’s global view. A fully distributed solution based on the weighted utility maximization optimizes resource allocation, keeping the interference from small cells to macrocells below predefined thresholds. The proposed algorithm considers the sDevices, which have both cellular and WiFi interfaces, and the wDevices which have WiFi-only interfaces. Numerical simulations substantiate the superiority of the proposed resource allocation algorithm, which increases significantly the average throughput and average utility of all devices, compared with the traditional and current methods. Throughput gains as large as 41.6% in spectral efficiency for the average of all sDevices and wDevices are achieved by the new designs. [ABSTRACT FROM PUBLISHER]

Determining tractable analytical expressions for the probability density functions (PDFs) of correlated Rayleigh random variables (i.e., the multivariate Rayleigh joint PDF) is a longstanding problem in wireless communications. Recent results have reported simpler forms for the 3-D and 4-D Rayleigh joint PDFs. Yet, the new solutions are still mathematically complex. New representations for the general 3-D Rayleigh and the general 4-D Rayleigh fading PDFs are derived. An advantage of the new representations is that only a single-integral computation is needed to compute the 3-D Rayleigh PDF and only double integral computation is needed for the 4-D Rayleigh PDF, where the integrals are proper and definite on $[0,\pi )$ and {[0,2\pi )} , respectively. The new expressions for the 3-D and 4-D Rayleigh PDFs are used to determine several special, “best” placements in the 2-D plane for three and four antennas. Closed-form solutions are found for three antennas with two or three independent antenna pairs, and four antennas with four or five independent antenna pairs. [ABSTRACT FROM AUTHOR]

Dynamic spectrum access (DSA) is a promising solution for enhancing the utilization efficiency of spectrum resources. In DSA, spectrum sensing is crucial and cooperative spectrum sensing has been confirmed as a promising technology that can combat the wireless channel fading problem. Most current works have assumed that the secondary users (SUs) are synchronous with the primary users' (PUs) network. However, on one hand, the SUs may have no information about the PUs' communication protocols. On the other hand, communications among the PUs are not based on synchronous operation in some systems. In order to address such problems, the DYWAMIT, an asynchronous wideband DSA system, is proposed. In this scheme, the SUs need not maintain synchronism with the PUs, enabling the SUs to cognitively and asynchronously access primary channels even without knowing the communication protocols of the PUs. Performance analysis and simulations are conducted to evaluate the proposed DYWAMIT algorithm; in particular, the average throughput of the SUs, accounting for the asynchronism between the SUs and PUs, is derived for four cases of interest. Some important future research challenges are highlighted. [ABSTRACT FROM PUBLISHER]

Controller placement is an important problem in software defined networks. Previously, some works addressed the problem by taking into account primary factors, such as propagation delay of control paths and capacity of controllers. Here, the problem is addressed from a novel standpoint of energy consumption, which is modeled as a binary integer program (BIP). In the BIP model, the energy consumption of the network that serves for the control traffic is minimized under the constraints of the delay of control paths and the load of controllers. In consideration of the high complexity of the BIP in large networks, a genetic heuristic algorithm is designed to find an effective sub-optimal solution. Simulation results show that the energy consumption of the heuristic algorithm is close to that of the BIP solution. No more than 4%, additional links are used by the heuristic algorithm if all the links have the same energy consumption. [ABSTRACT FROM PUBLISHER]

Packet collision is a well-known severe impairment in ALOHA-based networks and, more generally, in any random access network. As a consequence, several methodologies have been considered with the aim of lowering the resulting performance degradation. A novel multiuser detection scheme exploiting channel diversity to separate collided signals is proposed here to enable multiple packet reception capability in random access schemes. The performance of this approach is analytically derived and optimized in terms of network throughput, and compared with that of different alternatives. The overall performance in terms of throughput shows the effectiveness of the proposed scheme in different operating conditions. [ABSTRACT FROM AUTHOR]

A fast channel prediction scheme is proposed for Ricean fading scenarios. By employing an echo state network (ESN), the scheme is able to obtain smaller prediction error than previous designs. Simulation results show that the ESN prediction method has lower normalized mean squared error than the traditional autoregressive, discrete wavelet transform, and support vector machine prediction approaches. The symbol error rate gap between the perfect and predicted channel state information is small. [ABSTRACT FROM PUBLISHER]

Energy efficiency (EE) optimization of wireless systems has attracted increasing attention recently due to its beneficial impacts on the environment and operational savings. Max-min user energy-efficient precoding for multicell multiple-input–multiple-output (MIMO) cooperative networks is investigated. The optimization problem is a nonconvex fractional programming problem, and optimal solutions are hard to find. Two different local optimization methods, namely, block coordinate descent and sequential convex approximation, are proposed to transform the original problem into a series of convex subproblems. In the former method, the relationship between the user rate and the minimum mean square error (MMSE) is utilized, and optimization of the transmitter matrix is formulated as a semidefinite program; the latter method is based on the convex approximation of the nonconvex rate function. The fractional subproblem is transformed into a parameterized subtractive form by exploiting the generalized fractional programming theorem in both methods. Two iterative-fairness-based energy-efficient algorithms are proposed with proved local convergence. Numerical results illustrate that the proposed max-min EE algorithms can improve EE with a performance loss in terms of the sum rate at a high signal-to-noise ratio (SNR) and achieve EE fairness among base stations with different transmit power levels. [ABSTRACT FROM PUBLISHER]

Collaborative spectrum sensing is an effective method to improve detection rates in cognitive radio networks. However, it is vulnerable to spectrum sensing data falsification (SSDF) attacks when malicious secondary users (SUs) report fraudulent sensing data. In order to improve the robustness, numerous attack prevention schemes have been proposed to identify malicious SUs. Nevertheless, most of them neglect to incentivize SUs to send truthful reports. An incentive method based on peer-prediction is proposed to identify malicious suspects, punish attackers, and incentivize SUs to send truthful reports simultaneously for decision fusion. Moreover, continuous peer-prediction derived from the binary case is introduced, which is capable of preventing attacks in the continuous domain. Theoretical analysis and simulation results demonstrate that honest SUs are rewarded for accurate and truthful sensing results, while malicious SUs incur penalty for making falsified sensing reports. A significant improvement of detection rates is obtained by the proposed scheme when there are no more than half of malicious SUs conducting SSDF attacks. [ABSTRACT FROM PUBLISHER]

The physical layer beamforming design of downlink wireless energy transfer (WET) is investigated. To minimize the power of WET with respect to the terminals’ quality of service requirements, the physical beamforming design is modeled as a non-convex quadratically constrained quadratic program (QCQP) problem. A two-step method to solve the QCQP is proposed. First, the QCQP is tightened into an ellipsoidal approximation problem with the aid of a Löwner-John ellipsoid, by solving a semidefinite program (SDP). Second, due to the approximation problem’s ellipsoidal nature, it is solved as another SDP. The proposed method is compared using numerical results to the conventional semidefinite relaxation (SDR) approach. It is demonstrated that for equivalent computing time cost, the proposed method usefully improves the energy efficiency of the downlink WET compared with SDR. [ABSTRACT FROM PUBLISHER]