This paper proposes the base station ordering localization technique (BoLT) for emergency call localization in cellular networks. Exploiting the foreseen ultra-densification of the next-generation (5G and beyond) cellular networks, we utilize higher-order Voronoi tessellations to provide ubiquitous localization services that are in compliance to the public safety standards in cellular networks. The proposed localization algorithm runs at the base stations (BSs) and requires minimal operation from agents (i.e., mobile users). Particularly, BoLT requires each agent to feedback a neighbor cell list (NCL) that contains the order of neighboring BSs based on the received signal power in the pilots sent from these BSs. Moreover, this paper utilizes stochastic geometry to develop a tractable mathematical model to assess the performance of BoLT in a general network setting. The goal of this paper is to answer the following two fundamental questions: i) how many BSs should be ordered and reported by the agent to achieve a desirable localization accuracy? and ii) what is the localization error probability given that the pilot signals are subject to shadowing? Assuming that the BSs are deployed according to a Poisson point process (PPP), we answer these two questions via characterizing the tradeoff between the area of location region (ALR) and the localization error probability in terms of the number of BSs ordered by the agent. The results show that reporting the order of six neighboring BSs is sufficient to localize the agent within 10% of the cell area. Increasing the number of reported BSs to ten confines the location region to 1% of the cell area. This would translate to the range of a few meters to decimeters in the foreseen ultra-dense 5G networks.

We derive closed-form expressions for the achievable rates of a buffer-aided full-duplex (FD) multiple-input multipleoutput (MIMO) Gaussian relay channel. The FD relay still suffers from residual self-interference (RSI) after the application of self-interference mitigation techniques. We investigate both cases of a slow-RSI channel where the RSI is fixed over the entire codeword, and a fast-RSI channel where the RSI changes from one symbol duration to another within the codeword. We show that the RSI can be completely eliminated in the slow-RSI case when the FD relay is equipped with a buffer while the fast RSI cannot be eliminated. For the fixed-rate data transmission scenario, we derive the optimal transmission strategy that should be adopted by the source node and relay node to maximize the system throughput. We verify our analytical findings through simulations.

Point-of-Interest (POI) recommendation has attracted many interests recently because of its significant potential for helping users to explore new places and helping LBS providers to carry out precision marketing. Compared with the user-item rating matrix in conventional recommender systems, the user-location check-in matrix in POI recommendation is usually much more sparse, which makes the notorious cold start problem more prominent in POI recommendation. Trust-oriented recommendation is an effective way to deal with this problem but it requires that the recommender has access to user check-in and trust data. In practice, however, these data are usually owned by different businesses who are not willing to share their data with the recommender mainly due to privacy and legal concerns. In this paper, we propose a privacy-preserving framework to boost data owners willingness to share their data with untrustworthy businesses. More specifically, we utilize partially homomorphic encryption to design two protocols for privacy-preserving trustoriented POI recommendation. By offline encryption and parallel computing, these protocols can efficiently protect the private data of every party involved in the recommendation. We prove that the proposed protocols are secure against semi-honest adversaries. Experiments on both synthetic data and real data show that our protocols can achieve privacy-preserving with acceptable computation and communication cost.

This paper characterizes the performance metrics of MU-MIMO systems under Rayleigh fading channels in the presence of both cochannel interference and additive noise with unknown channel state information and known correlation matrices. In the first task, we derive analytical expressions for the cumulative distribution function of the instantaneous signal-to-interference-plus-noise ratio (SINR) for any deterministic beamvectors. As a second task, exact closed-form expressions are derived for the instantaneous capacity, the upper bound on ergodic capacity, and the Gram-Schmidt orthogonalization-based ergodic capacity for similar intra-cell correlation coefficients. Finally, we present the utility of several structured-diagonalization techniques, which can achieve the tractability for the approximate solution of ergodic capacity for both similar as well as different intra-cell correlation matrices. The novelty of this paper is to formulate the received SINR in terms of indefinite quadratic forms, which allows us to use complex residue theory to characterize the system behavior. The analytical expressions obtained closely match simulation results.

This paper investigates the secrecy performance of a two-user downlink non-orthogonal multiple access systems. Both single-input and single-output and multiple-input and singleoutput systems with different transmit antenna selection (TAS) strategies are considered. Depending on whether the base station has the global channel state information of both the main and wiretap channels, the exact closed-form expressions for the secrecy outage probability (SOP) with suboptimal antenna selection and optimal antenna selection schemes are obtained and compared with the traditional space-time transmission scheme. To obtain further insights, the asymptotic analysis of the SOP in high average channel power gains regime is presented and it is found that the secrecy diversity order for all the TAS schemes with fixed power allocation is zero. Furthermore, an effective power allocation scheme is proposed to obtain the nonzero diversity order with all the TAS schemes. Monte-Carlo simulations are performed to verify the proposed analytical results.

Non-orthogonal multiple access (NOMA) is promoted as a key component of 5G cellular networks. As the name implies, NOMA operation introduces intracell interference (i.e., interference arising within the cell) to the cellular operation. The intracell interference is managed by careful NOMA design (e.g., user clustering and resource allocation) along with successive interference cancellation. However, most of the proposed NOMA designs are agnostic to intercell interference (i.e., interference from outside the cell), which is a major performance limiting parameter in 5G networks. This article sheds light on the drastic negative-impact of intercell interference on the NOMA performance and advocates interference-aware NOMA design that jointly accounts for both intracell and intercell interference. To this end, a case study for fair NOMA operation is presented and intercell interference mitigation techniques for NOMA networks are discussed. This article also investigates the potential of integrating NOMA with two important 5G transmission schemes, namely, full duplex and device-to-device communication. This is important since the ambitious performance defined by the 3rd Generation Partnership Project (3GPP) for 5G is foreseen to be realized via seamless integration of several new technologies and transmission techniques.

Complex wireless transmission systems require multi-dimensional joint statistical techniques for performance evaluation. Here, we first present the exact closed-form results on order statistics of any arbitrary partial sums of Gamma random variables with the closedform results of core functions specialized for independent and identically distributed Nakagami-m fading channels based on a moment generating function-based unified analytical framework. These both exact closed-form results have never been published in the literature. In addition, as a feasible application example in which our new offered derived closed-form results can be applied is presented. In particular, we analyze the outage performance of the finger replacement schemes over Nakagami fading channels as an application of our method. Note that these analysis results are directly applicable to several applications, such as millimeter-wave communication systems in which an antenna diversity scheme operates using an finger replacement schemes-like combining scheme, and other fading scenarios. Note also that the statistical results can provide potential solutions for ordered statistics in any other research topics based on Gamma distributions or other advanced wireless communications research topics in the presence of Nakagami fading.

Error performance is considered as one of the most important performance measures, and deriving the closed-form expressions for efficient modulation techniques over generalized fading channels is important for future cellular systems. In this paper, the performance of a dual-hop amplify-and-forward multi-relay system with best relay selection is analyzed over independent and non-identically distributed (i.n.i.d.) Nakagami-m fading links with both integer and non-integer fading parameters. The impact of practical constraints of imperfect channel state information (CSI) and non-linear power amplifier (NLPA) at each of the relays are considered. Closed-form expressions for the outage probability are derived for both integer and non-integer fading parameters, and asymptotic analysis on the outage probability is performed to obtain the diversity order of the considered multi-relay system. Based on the cumulative distribution function approach, average symbol error rate (ASER) expressions for general order hexagonal QAM, general order rectangular QAM, and 32-cross QAM schemes are also derived. The comparative analysis of ASER for various QAM schemes with different constellations is also illustrated. Furthermore, the impact of the number of relays, fading parameter, channel estimation error, and non-linear distortion on the system performance is also highlighted. Finally, the derived analytical results are validated through Monte-Carlo simulations.

This paper focuses on the detection of non-recurrent traffic anomaly caused by unexpected or transient incidents, such as traffic accidents, celebrations, and disasters. Comparing to existing approaches, it considers the spatial and temporal propagation of traffic anomalies from one road to other neighbor roads by proposing an STLP-OD framework. The experimental results on a real data set show that the proposed approach can improve the accuracy of traffic outlier detection baselines significantly.

The number of applications (apps) available for smart devices or Android based IoT (Internet of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill-designed or malicious apps (malapps) has been growing explosively. To ensure the quality and security of the apps in the markets, many approaches have been proposed in recent years to discriminate malapps from benign ones. Machine learning is usually utilized in classification process. Accurately characterizing apps' behaviors, or so-called features, directly affects the detection results with machine learning algorithms. Android apps evolve very fast. The size of current apps has become increasingly large and the behaviors of apps have become increasingly complicated. The extracting effective and representative features from apps is thus an ongoing challenge. Although many types of features have been extracted in existing work, to the best of our knowledge, no work has systematically surveyed the features constructed for detecting Android malapps. In this paper, we are motivated to provide a clear and comprehensive survey of the state-of-the-art work that detects malapps by characterizing behaviors of apps with various types of features. Through the designed criteria, we collect a total of 1947 papers in which 236 papers are used for the survey with four dimensions: the features extracted, the feature selection methods employed if any, the detection methods used, and the scale of evaluation performed. Based on our in-depth survey, we highlight the issues of exploring effective features from apps, provide the taxonomy of these features and indicate the future directions.