This paper deals with the problem of determining the optimal angle in a conventional double-beams tilting (CDT) using multiple vertical beams in a single cell scenario. In order to solve this problem, we present a novel interference algorithm called the K means Interference Avoidance Algorithm (KIA). Furthermore, we propose the Fractional Frequency Double Beams Tilting (FFDT) scheme by segmenting the frequency band to alleviate the Inter Beam interference (IBI) and the load imbalance problem between the beams occurring in the CDT. In particular, the special case of KIA provides a solution for FFDT and CDT, which is shown to be the quasi-optimal solution. Finally, this paper shows both cell throughput and load balancing performance over System Level Simulation (SLS) for performance evaluation of the proposed algorithm.

In this paper, the system-level performance is evaluated for the feedback scheme on the Precoding Matrix Index (PMI) and Channel Quality Indication (CQI), which are required for user selection in the multi-user MIMO system. Our analysis demonstrates that the number of users, the number of selected users, and codebook size are the key factors that govern the performance of the Best Companion Grouping (BCG)-based user scheduling. Accordingly, we have confirmed that the probability of forming the co-scheduled user group is determined by these factors, implying that the number of PMI’s and codebook size can be dynamically determined to maximize the average system throughput subject to the given feedback overhead, as the number of users varies in the cell.

Enhanced confidentiality is a major concern for most communication fields including personal, military, and governmental applications. Conventionally, confidentiality is guaranteed by encryption and corresponding decryption so that the encrypted data can only be decrypted by intended receivers. However, both encryption and decryption processes include high complexity and heavy signaling overhead due to key distribution and agreement protocol. Thus, in order to overcome high complexity and heavy signaling, the Physical Layer Security (PLS) has been proposed as a prospective solution to enhance confidentiality against eavesdroppers by physical layer techniques. This paper proposes a novel physical layer security technique that adopts the Adaptive and Rotated Transmission (ART) scheme based on the instantaneous channel information, i.e., magnitude and channel phase in order to achieve secure transmission. The performance of our proposed transmission scheme is evaluated through mathematical analysis and numerical results, showing a meaningful improvement in confidentiality.

To achieve high spectral efficiency, a modern cellular network such as LTE or 5G New Radio (NR) aims to operate with full frequency reuse. This deployment will significantly increase the level of Co-Channel Interference (CCI) for cell-edge User Equipments (UEs), and the CCI has become a major throughput-limiting factor. Thus, the suppression of CCI in the 5G network is the most important feature to increase downlink throughput. In order to mitigate CCI, Interference Whitening (IW) is an effective low-complexity linear method to suppress colored interference in a MIMO-OFDM system. However, conventional IW can degrade the performance when the noise-dominant environment due to limited samples, e.g., DMRS (De-Modulation Reference Signal). To address that, we propose a Reinforcement Learning based Interference Whitening (RL-IW) that adaptively controls the IW mode by learning algorithm. The experimental results show that RL-IW has performance gain in terms of both BLER (Block Error Rate) and downlink throughput than conventional IW.

In this paper, 150W multi parallel LDC system, different from integral type LDC system of the conventional electric vehicle is proposed. The high efficiency LDC system is designed by reducing the losses of the magnetic element and semiconductor element by lowering the rated capacity through power sharing. Also, LDC is designed as active clamp forward converter to reduce the loss caused by the reset winding of transformer. And the center tap transformer is applied to reduce the loss due to the current, so the efficiency is increased. The high efficiency of the proposed parallel type LDC is verified by experiments.

An adaptive control scheme of digital loop filter for automatic frequency control (AFC) is proposed to improve LTE downlink throughput in high-speed train (HST) channel. A mobile device in HST channel suffers from performance degradation due to the abrupt change in Doppler shift. In this case, a higher loop gain is desirable to quickly track the Doppler shift. However, in general, there is a fundamental trade-off between locking time and phase jitter performance in AFC. Therefore, it is crucial to identify the channel condition for adjusting AFC loop gain. In this paper, a wireless channel classification problem is formulated and the optimal classifier is derived by using support vector machine (SVM) algorithm. In particular, HST and non-HST channel environments are classified by exploiting the statistical distribution of the phase estimates. Experimental results show that the SVM-based adaptive loop gain control improves the throughput in HST channel.

In distributed query processing systems where caching infrastructure is distributed and scales with the number of servers, it is becoming more important to orchestrate and leverage a large number of cached objects in distributed caching systems seamlessly as the present trend is to build large scalable distributed systems by connecting small heterogeneous machines. With a large scale distributed caching system, a scheduling policy must consider both cache hit ratio and system load balance to optimize multiple queries. A scheduling policy that considers system load but not cache hit ratio often fails to reuse cached data by not assigning a query to the sever that has data objects the query needs. On the contrary, a scheduling policy that considers cache hit ratio but not system load balance may suffer from system load imbalance. To maximize the overall system throughput and to reduce query response time, a multiple query scheduling policy must balance system load and also leverage cached objects. In this paper, we present a distributed query processing framework that exhibits high cache hit ratio while achieving good system load balance. In order to seamlessly manage our distributed scalable caching system, our framework performs autonomic cached data migrations to improve cache hit ratio. Our experiments show that our proposed query scheduling policy and data migration policy significantly improve system throughput by achieving high cache hit ratio while avoiding system load imbalance.

Mobile computing and sensing technologies present exciting opportunities for healthcare. Prescription wireless sensors worn by patients can automatically deliver medical data to care providers, dramatically improving their ability to diagnose, monitor, and manage a range of medical conditions. Using the mobile phones that patients already carry to provide connectivity between sensors and providers is essential to keeping costs low and deployments simple. Unfortunately, software-based attacks against phones are also on the rise, and successful attacks on privacy-sensitive and safety-critical applications can have significant consequences for patients.

Mobile sensing technologies present exciting opportunities for healthcare. Wireless sensors can automatically provide sensor data to care providers, dramatically improving their ability to diagnose, monitor, and manage a wide range of medical conditions. Using mobile phones to provide connectivity between sensors and providers is essential to keeping costs low and deployments simple. Unfortunately, software-based attacks against phones, which can have significant consequences for patients, are also on the rise.

Mobile medical sensors promise to provide an efficient, accurate, and economic way to monitor patients' health outside the hospital. Patient authentication is a necessary security requirement in remote health monitoring scenarios. The monitoring system needs to make sure that the data is coming from the right person before any medical or financial decisions are made based on the data. Credential-based authentication methods (e.g., passwords, certificates) are not well-suited for remote healthcare as patients could hand over credentials to someone else. Furthermore, one-time authentication using credentials or trait-based biometrics (e.g., face, fingerprints, iris) do not cover the entire monitoring period and may lead to unauthorized post-authentication use. Recent studies have shown that the human electrocardiogram (ECG) exhibits unique patterns that can be used to discriminate individuals. However, perturbation of the ECG signal due to physical activity is a major obstacle in applying the technology in real-world situations. In this paper, we present a novel ECG and accelerometer-based system that can authenticate individuals in an ongoing manner under various activity conditions. We describe the probabilistic authentication system we have developed and present experimental results from 17 individuals.

More than 100 million Americans are currently living with at least one chronic health condition and expenditures on chronic diseases account for more than 75 percent of the $2.3 trillion cost of our healthcare system. To improve chronic illness care, patients must be empowered and engaged in health

In people-centric opportunistic sensing, people offer their mobile nodes (such as smart phones) as platforms for collecting sensor data. A sensing application distributes sensing 'tasks', which specify what sensor data to collect and under what conditions to report the data back to the application. To perform a task, mobile nodes may use on-board sensors, a body-area network of personal sensors, or sensors from neighboring nodes that volunteer to contribute their sensing resources. In all three cases, continuous sensor monitoring can drain a node's battery. We propose DEAMON (Distributed Energy-Aware MONitoring), an energy-efficient distributed algorithm for long-term sensor monitoring. Our approach assumes only that mobile nodes are tasked to report sensor data under conditions specified by a Boolean expression, and that a network of nearby sensor nodes contribute to monitoring subsets of the task's sensors. Our algorithm to select sensor nodes and to monitor the sensing condition conserves energy of all nodes by limiting sensing and communication operations. We evaluate DEAMON with a stochastic analysis and with simulation results, and show that it should significantly reduce energy consumption.

Personal mobile devices are increasingly equipped with the capability to sense the physical world (through cameras, microphones, and accelerometers, for example) and the, network world (with Wi-Fi and Bluetooth interfaces). Such devices offer many new opportunities for cooperative sensing applications. For example, users' mobile phones may contribute data to community-oriented information services, from city-wide pollution monitoring to enterprise-wide detection of unauthorized Wi-Fi access points. This people-centric mobile-sensing model introduces a new security challenge in the design of mobile systems: protecting the privacy of participants while allowing their devices to reliably contribute high-quality data to these large-scale applications.

We consider the channel assignment problem for multihop wireless networks in which nodes have multiple interfaces. Given the number of interfaces at each node and available channels in the system, we find a feasible channel assignment to improve network performance. Even when routing is given, finding a channel assignment for optimal performance is NP-hard. We present the SAFE (skeleton assisted partition FrEe) channel assignment scheme, which uses randomized channel assignment in a distributed manner while maintaining network connectivity. SAFE can utilize all independent channels in the system while attempting to distribute edges sharing a particular channel evenly throughout the network. To handle topology change and incremental deployment better, SAFE decouples the channel assignment problem from routing. Our simulation results show that SAFE significantly improves network performance in terms of throughput and delay and is comparable to the best prior centralized scheme that jointly considers routing and channel assignment

A variety of wireless technologies have been standardized and commercialized, but no single technology is considered the best because of different coverage and bandwidth limitations. Thus, interworking between heterogeneous wireless networks is extremely important for ubiquitous and high-performance wireless communications. Security in interworking is a major challenge due to the vastly different security architectures used within each network. The goal of this paper is twofold. First, we provide a comprehensive discussion of security problems and current technologies in 3G and WLAN systems. Second, we provide introductory discussions about the security problems in interworking, the state-of-the-art solutions, and open problems.

User mobility in wireless data networks is increasing because of technological advances, and the desire for voice and multimedia applications. These applications, however, require fast handoffs between base stations to maintain the quality of the connections. Previous work on context transfer for fast handoffs has focused on reactive methods, i.e. the context transfer occurs after the mobile station has associated with the next base station or access router. In this paper, we describe the use of a novel and efficient data structure, neighbor graphs, which dynamically captures the mobility topology of a wireless network as a means for prepositioning the station's context ensuring that the station's context always remains one hop ahead. From experimental and simulation results, we find that the use of neighbor graphs reduces the layer 2 handoff latency due to reassociation by an order of magnitude from 15.37ms to 1.69ms, and that the effectiveness of the approach improves dramatically as user mobility increases.

We consider a design of quasicyclic LDPC codes which have irregular column weights. We derive bit-oriented bound and parity-oriented bound on the minimum distances of irregular quasicyclic codes using a similar technique to Tanner's simple lower bound

The 802.11 IEEE Standard has enabled low cost and effective wireless LAN services (WLAN). With the sales and deployment of WLAN based networks exploding, many people believe that they will become the fourth generation cellular system (4G) or a major portion of it. However, the small cell size of WLAN creates frequent hand-offs for mobile users. If the latency of these hand-offs is high, as previous studies have shown, then the users of synchronous multimedia applications such as voice over IP (VoIP) will experience excessive jitter. The dominating factor in WLAN hand-offs has been shown to be the discovery of the candidate set of next access points. In this paper, we describe the use of a novel and efficient discovery method using neighbor graphs and non-overlap graphs. Our method reduces the total number of probed channels as well as the total time spent waiting on each channel. Our implementation results show that this approach reduces the overall probe time significantly when compared to other approaches. Furthermore, simulation results show that the effectiveness of our method improves as the number of non-overlapping channels increases, such as in the 5 GHz band used by the IEEE 802.11a standard.