Satellite communication has become essential for achieving seamless global connectivity in the 5 G and the future 6G networks. However, preventing eavesdropping attacks on data transmission remains a challenge due to the broadcasting nature of radio signals. Physical layer security (PLS) is a promising approach that can offer a lightweight solution suitable for satellites with hardware constraints such as limited computing and processing power. Recent studies considering PLS techniques have investigated secrecy performance in various satellite communication environments such as non-orthogonal multiple access but multi-satellite scheduling problems have been less highlighted. Particularly, in this paper, we investigate secrecy outage probability in low Earth orbit satellite networks by jointly considering multi-satellite scheduling for data and artificial noise transmissions against eavesdropping attacks. We propose a novel multi-satellite scheduling scheme and derive a closed-form of secrecy outage probability over Nakagami-$m$fading channels. We verify our analysis and evaluate our proposed scheme compared to several baseline schemes through extensive simulations.

Cellular networks such as 4G and 5G have been exceedingly successful, but have encountered a parallel surge in security threats. Random access (RA) is an essential procedure performed between a user and a base station to facilitate attachment to the network and obtaining radio resources for downlink and uplink transmissions. Particularly, users get tightly synchronized to the base station based on the timing advance (TA) command that estimates propagation delay over the air during the RA procedure. In this paper, we investigate security issues related to the transmission and reception of TA information, and scheduled uplink transmission during the RA procedure in cellular networks. Furthermore, we present a random access failure attack that forces TA misalignment to users and thus results in service failure of legitimate users in the network. Finally, we verify our analysis through software-defined radio (SDR) based experiments.

Cellular networks have been successfully evolved over the decades. Especially, Long-Term Evolution (LTE) has been exceedingly successful and the security threats against LTE systems have increased rapidly. Particularly,trackingLTE user devices has been shown to be effective as thetemporaryuser identifiers (IDs) are easily extracted and used to locate targeted devices by passive eavesdroppers. We notice that naive approaches, such as frequent updates of temporary user IDs, areinsufficientto mitigate user-tracking attacks since the new and old temporary IDs for the same user device are easilylinkableby adversaries who can measure the wireless channel characteristics between the user device and herself. In this paper, we propose an opportunistic uplink power control scheme to minimize the probability of successful user tracking by an adversary whose location is unknown. We devise the notion of average inference error probability in order to measure the level of users’ location privacy. Moreover, we derive the closed-form expression of the approximated average inference error probability and formulate an optimization problem to maximize the average inference error probability under a constraint of an allowable power budget for each user. Against a passive adversary, our proposed power control scheme effectively degrades an adversary’s inference ability by 50% when 10 users are scheduled in each transmission time slot, which will lead to almost 100% inference error at the adversary over multiple time slots.

Cellular networks have been successfully evolved over the decades. Especially, Long-Term Evolution (LTE) has been exceedingly successful and the security threats against LTE systems have increased rapidly. Particularly, tracking LTE user devices has been shown to be effective as the temporary user identifiers (IDs), which are used in LTE systems to indicate LTE user devices in the system, are easily extracted and used to locate targeted devices by passive eavesdroppers. In this paper, we investigate the impact of uplink power control on the probability of successful user tracking by an adversary whose location is unknown. We devise the notion of average inference error probability in order to measure the level of users’ location privacy. Moreover, we derive the closed-form expression of the approximated average inference error probability and formulate an optimization problem for maximizing the average inference error probability under a constraint of an allowable power budget for each user. For defense, we propose a power control scheme able to effectively degrade an adversary’s inference ability by 50% when 10 users are scheduled in each transmission time slot, which will result in almost 100% inference error at the adversary over multiple time slots.

Simultaneous wireless information and power transfer (SWIPT) has been considered one of the emerging techniques to overcome power limitation of wireless devices using batteries as well as to send information at the same time. Although the SWIPT techniques have been intensively investigated, the fairness among wireless-powered devices in the SWIPT-enabled multicell networks has not been studied yet. In this paper, we propose an adaptive proportional fairness ( α-PF) scheduling algorithm in SWIPT-enabled multi-cell downlink networks. We define an adjustable weighted sum of achievable rate and harvested energy as the utility function of each user and investigate fairness among utilities of users. Through extensive simulations, we evaluate the proposed scheduling algorithm in terms of rate-energy (RE) tradeoff, the fairness of achievable rate and harvested energy. Compared to various existing scheduling algorithms such as random scheduling, maximum signal-to-interference-plus-noise (SINR) scheduling, and α-adaptive scheduling algorithms, the proposed scheduling algorithm achieves better fairness measure (e.g., Jain's fairness index). In addition, we can adaptively control parameters of the proposed scheduling algorithm to satisfy certain requirements of the system.

The proliferation of surveillance cameras has greatly improved the physical security of many security-critical properties including buildings, stores, and homes. However, recent surveillance camera looping attacks demonstrate new security threats --- adversaries can replay a seemingly benign video feed of a place of interest while trespassing or stealing valuables without getting caught. Unfortunately, such attacks are extremely difficult to detect in real-time due to cost and implementation constraints. In this paper, we propose SurFi to detect these attacks in real-time by utilizing commonly available Wi-Fi signals. In particular, we leverage that channel state information (CSI) from Wi-Fi signals also perceives human activities in the place of interest in addition to surveillance cameras. SurFi processes and correlates the live video feeds and the Wi-Fi CSI signals to detect any mismatches that would identify the presence of the surveillance camera looping attacks. SurFi does not require the deployment of additional infrastructure because Wi-Fi transceivers are easily found in the urban indoor environment. We design and implement the SurFi system and evaluate its effectiveness in detecting surveillance camera looping attacks. Our evaluation demonstrates that SurFi effectively identifies attacks with up to an attack detection accuracy of 98.8% and 0.1% false positive rate.

Simultaneous wireless information and power transfer (SWIPT) is a promising technique to transmit information and harvest energy at the same time. In this paper, we investigate multiuser scheduling criteria in a multiuser SWIPT system taking into account co-channel interference in a multicell environment, where each transmitter operate independently. We propose an α-adaptive scheduling scheme, which is able to adjust a scheduling criterion between maximizing achievable rate and maximizing harvested energy of the scheduled device by adjusting α factor. Employing a power splitting receiver, we derive closed-form analytical results including cumulative distribution function (CDF) of the harvested energy, CDF of the achievable rate, average harvested energy, and average achievable rate. We also investigate the effect of adjustable α factor in the proposed scheduling scheme and multiuser diversity in terms of the CDF of the harvested energy, the CDF of the achievable rate, and rate-energy tradeoff, compared with two conventional scheduling schemes: random scheduling and max-SNR scheduling. Our analytical results provide insightful information for designing multiuser scheduling criteria considering co-channel interference in the SWIPT systems.

In this paper, we introduce the notions of a user-scaling function and a user-scaling exponent and multiuser diversity (UEMD) pair. Our notions for the UEMD pair could be utilized as a basic tool for analyzing user-scaling laws. We derive a secure user-scaling law in terms of SNR, the number of eavesdroppers, the number of distributed antennas in distributed antenna systems, and design parameter λ. Through analytical and numerical results, we characterize the effect of the number of distributed antennas on the user-scaling behavior in terms of achievable secrecy rate. Compared with the conventional results based on a single antenna system, our results indicate that installing a small number of distributed antennas could provide a significant performance gain in terms of the achievable secrecy rate.

Recently, study on designing a new metric to express quality of experience (QoE) has attracted attention since user satisfaction may be different according to the types of served traffic. The utility function for various traffic has been studied for many years and most of the previous work focused on the utility functions with respect to a single performance metric such as throughput. However, multiple performance metrics may affect user satisfaction according to user properties or situations. One of critical factors that affect the sensitivity of user satisfaction is the remaining battery energy. In this paper, we investigate the characteristics of the user satisfaction with respect to throughput and energy efficiency considering the remaining battery energy. Based on the characteristics, we design a multi-variable QoE function based on the unified utility, especially, considering user's remaining battery energy and verify the feasibility of the proposed multi-variable QoE function through numerical results.

In this paper, we propose an opportunistic user selection criterion to obtain a multiuser diversity gain for secure communication. At the same time, we also propose a strategy for utilizing a small base station in heterogeneous networks as a helper or a jammer adaptively. Our approach is to maximize the secrecy achievable rate based on an analytically derived lower bound instead of the original objective function due to its complexity. Based on a simple proposed user selection criterion considering both macro and small base stations, we propose two jamming strategies according to knowledge of eavesdropper's channel: adaptive jamming and probabilistic jamming strategies. Through simulations in two scenarios, it is shown that our proposed user selection and jamming schemes provide a good performance gain in terms of secrecy achievable rate.

Due to spectrum shortage in the conventional microwave bands, millimeter wave (mmWave) bands have been attracting great attention as an additional spectrum band for 5G cellular networks. In this paper, we show the feasibility of using a mmWave-based small cell with directional antennas. We investigate the effect of the number of antennas, nant, on the capacity and coverage probability, and propose an antenna clustering scheme (ACS) to utilize the antennas more efficiently. For a given nant, we also investigate the effect of the number of clusters, ncluster, on the capacity and coverage probability. In addition, we propose two design criteria: a capacity-maximization criterion (CapMC) and a coverage-maximization criterion (CovMC), in the mmWave-based small cell. Each design criterion is formulated as a joint optimization problem to find the optimal values of nantand nclusterto maximize each objective function while satisfying system requirements such as capacity and coverage probability. Performance evaluation shows that CapMC can achieve the highest capacity while satisfying a given coverage probability requirement and CovMC can achieve the highest coverage probability while satisfying a given capacity requirement.

The hierarchical cooperation (HC) scheme is known to exhibit linear scaling from the viewpoint of information theory under the assumption of no control and data frame overhead. However, if we consider the control and data frame overheads of the HC scheme in a more practical ad-hoc network environment, the scaling law of the aggregate throughput is expected to be far from linear scaling. In this paper, we observe the effect of the control and data frame overheads on the capacity scaling of the HC scheme. From the results of performance evaluation, we find that the data frame overhead only affects the degradation of the aggregate throughput in proportion to the data frame overhead ratio. Moreover, the control overhead affects the trend of the aggregate throughput. The slope of the aggregate throughput converges to near zero as the total number of nodes, N, increases, and the aggregate throughput becomes saturated for any given number of stages, h. The significant performance degradation in the aggregate throughput is inevitable due to the control and data frame overheads. Therefore, it is not always good to use as many stages as possible, and, thus, there exists an optimal number of stages according to the given system parameters.

In emergency situations such as a disaster and a blackout, machine nodes should report emergency alarms, including the disaster type and disaster area to an M2M server. When many related machine nodes attempt a random access (RA) to report emergency alarms, and this may cause a physical random access channel (PRACH) overload. In this case, the machine nodes hardly access the network within a given delay requirement of emergency alarms. In this paper, we propose a novel random access scheme based on a special preamble for emergency indication in an emergency situation and adaptively reserve more PRACH resources in proportion to the number of machine nodes using the special preamble. The proposed RA scheme outperforms the conventional RA scheme in terms of access delay and can accommodate much more machine nodes in emergency situations, compared with the conventional RA scheme.

Machine-to-machine (M2M) communications exhibit quite different characteristics, compared with human-to-human (H2H) communications. Since the number of M2M devices is much larger than that of users for H2H communications, it may cause a shortage problem of radio resources if we do not consider an efficient radio resource management scheme. In this paper, we propose an efficient resource allocation scheme to support a large number of M2M devices in the network. First, we investigate the tradeoff relationship between a non-orthogonal resource allocation scheme based on user-pairing and an orthogonal resource allocation scheme by considering pilot overhead in resource usage. Second, we set up an optimization problem for minimizing the amount of allocated resources for a large number of devices in the network. Finally, we propose a user-pairing based resource allocation algorithm. When the number of devices is 500 and the average SNR is set to 10 dB, our proposed suboptimal minimum resource allocation (SMRA) scheme reduces the total required number of resource blocks by 29% and 28%, compared with the orthogonal resource allocation (ORA) scheme and the random user-pairing based resource allocation (RUPRA) scheme, respectively.

Small-cell networks are expected as one of key solutions for high system capacity. However, self-organizing and self-healing mechanisms are necessarily required to deploy and manage an increasing number of small-cell networks. In this paper, we consider a future small-cell network as an intelligent distributed antenna system such as an adaptive array antenna. We propose a self-organizing mechanism and a self-healing mechanism for small-cell networks through cooperative clusters. We evaluate the system performance in terms of resource utilization in both normal and failure cases of a small-cell network. The results show that proposed mechanisms outperform the conventional mechanisms.

The conventional hierarchical cooperation (HC) scheme proposed by Ozgur et al. [1] is a novel communication scheme that can achieve linear capacity scaling, O(N) in wireless ad-hoc network from the viewpoint of information theory without considering control and data overhead. In this paper, we investigate the effects of practical parameters such as packet arrival rate, control overhead and data overhead on the HC scheme. We formulate an aggregate throughput optimization problem in terms of cluster size m and solve it by well-known algorithms. Through the performance evaluations, we observe three main effects of the practical parameters. First, large data overhead ratio degrades the aggregate throughput. 31% performance degradation occurs when we consider data overhead ratio α = 0:45. Second, large control overhead also degrades the aggregate throughput and affects to determine the cluster size m for maximum aggregate throughput. Third, the packet arrival rate λ plays a key factor for system stability and we obtain a sufficient condition for system stability.

An inter-cell interference (ICI) problem between co-channel BSs has been one of main challenging research issues in downlink cellular networks. Fractional frequency reuse (FFR) and BS cooperation are useful techniques to manage the ICI problem. By combining the BS cooperation and FFR techniques, we propose to determine an efficient cooperation mode and the type of subchannels, i.e., reusable subchannels or exclusively used subchannels. The optimization problem to minimize the total power consumption in a cooperative cluster is formulated while satisfying a given constraint in terms of the number of subchannels. When the number of users is 20, our proposed energy-efficient subchannel allocation (EESA) scheme consumes 21%, 25%, 43%, and 43% less power than the conventional resource minimization (RM), fractional frequency reuse (FFR), exclusive (EX), and full cooperation (FCO) scheme respectively. Moreover, our proposed EESA scheme outperforms the other four schemes in terms of outage probability.