This paper studies the energy-saving problem in cognitive multicast orthogonal frequency-division multiplexing (OFDM) systems, for which a time-frequency two-dimensional model is established to enable the system energy conservation through joint temporal and spectral adaptations. The formulated two-dimensional problem, minimizing the total power consumption whilst guaranteeing the minimal-rate requirement for each multicast session and constraining the maximal perceived interference in each timeslot for the active primary user, is categorized as mixed integer non-convex programming, whose optimal solution is intractable in general. However, based on the time-sharing property, an asymptotically optimal algorithm is proposed by jointly iterating spectrum element (SE) assignment and power allocation. Moreover, a suboptimal algorithm, which carries out SE assignment and power allocation sequentially, is presented as well to reduce the computation complexity. Simulation results show the proposed joint algorithm can achieve the near-optimal solution, and the proposed sequential algorithm approximates to the joint one very well with a gap of less than 3%. Compared with the existing slot-by-slot energy-saving algorithms, the total power consumption is considerably decreased due to the combined exploitation of time and frequency dimensions.

Recently, the growing concepts that information communication technologies apply to social infrastructures have caused deep interests with wireless sensor networks (WSNs). WSNs can be used for various application areas such as home, health, factory and so on. For the different application areas, there are different technical issues (e.g., security, reliability, real time gathering, long life time, scalability). Efficient information gathering can be potentially obtained if we take a suitable information gathering method with considering the requirements of each WSN application. Thus, we have not persisted all information gathering perfectly and have proposed one of simple information gathering methods in response to the requirements of WSN applications in this paper. In the proposed method, the information is converted to physical-layer parameters of wireless communications, such as frequency and time. Also, simulations are performed to validate the effectiveness of the proposed method in real time gathering and estimating with high precision.

In recent years, the time variation of Internet traffic has increased due to the growth of streaming and cloud services. Backbone networks must accommodate such traffic without congestion. Traffic engineering with traffic prediction is one approach to stably accommodating time-varying traffic. In this approach, routes are calculated from predicted traffic to avoid congestion, but predictions may include errors that cause congestion. We propose prediction-based traffic engineering that is robust against prediction errors. To achieve robust control, our method uses model predictive control, a process control method based on prediction of system dynamics. Routes are calculated so that future congestion is avoided without sudden route changes. We apply calculated routes for the next time slot, and observe traffic. Using the newly observed traffic, we again predict traffic and re-calculate the routes. Repeating these steps mitigates the impact of prediction errors, because traffic predictions are corrected in each time slot. Through simulations using backbone network traffic traces, we demonstrate that our method can avoid the congestion that the other methods cannot.

What should be the ultimate form of the cloud computing environment? The solution should have two important features; “Fine-Granularity” and “Participation.” To realize an attractive and feasible solution with these features, we propose a “participating fine-grained cloud computing platform” that a large number of personal or small-company resource suppliers participate in, configure and provide cloud computing on. This enables users to be supplied with smaller units of resources such as computing, memory, content, and applications, in comparison with the traditional Infrastructure as a Service (IaaS). Furthermore, to search for nearby resources efficiently among the many available on the platform, we also propose Resource Breadcrumbs (RBC) as a key technology of our proposed platform to provide in-network guidance capability autonomously for users' queries. RBC allows supplier-nodes to distribute guidance information directed to themselves with dedicated control messages; in addition, the information can be logged along the trail of message from supplier to user. With this distributed information, users can to autonomously locate nearby resources. Distributed management also reduces computational load on the central database and enables a participating fine-grained cloud platform at lower cost.

In this paper, we propose an error-correction low-pass filter (EC-LPF) algorithm for estimating the wireless distance between devices. To measure this distance, the received signal strength indication (RSSI) is a popularly used method because the RSSI of a wireless signal, such as Wi-Fi and Bluetooth, can be measured easily without the need for additional hardware. However, estimating the wireless distance using an RSSI is known to be difficult owing to the occurrence of inaccuracies. To examine the inaccuracy characteristics of Bluetooth RSSI, we conduct a preliminary test to discover the relationship between the actual distance and Bluetooth RSSI under several different environments. The test results verify that the main reason for inaccuracy is the existence of measurement errors in the raw Bluetooth RSSI data. In this paper, the EC-LPF algorithm is proposed to reduce measurement errors by alleviating fluctuations in a Bluetooth signal with responsiveness for real-time applications. To evaluate the effectiveness of the EC-LPF algorithm, distance accuracies of different filtering algorithms are compared, namely, a low-pass filer (LPF), a Kalman filter, a particle filter, and the EC-LPF algorithm under two different environments: an electromagnetic compatibility (EMC) chamber and an indoor hall. The EC-LPF algorithm achieves the best performance in both environments in terms of the coefficient of determination, standard deviation, measurement range, and response time. In addition, we also implemented a meeting room application to verify the feasibility of the EC-LPF algorithm. The results prove that the EC-LPF algorithm distinguishes the inside and outside areas of a meeting room without error.

A new approach to reconstructing antenna far-field patterns from the missing part of the pattern is presented in this paper. The antenna far-field pattern can be reconstructed by utilizing the iterative Hilbert transform, which is based on the relationship between the real and imaginary part of the Hilbert transform. A moving average filter is used to reduce the errors in the restored signal as well as the computation load. Under the constraint of the causality of the current source in space, we could successfully reconstruct the data. Several examples dealing with line source antennas and antenna arrays are simulated to illustrate the applicability of this approach.

Dense millimeter-wave networks are a promising candidate for next-generation cellular systems enabling multiple gigabit-per-second data rates. A major disadvantage of millimeter-wave systems is signal disruption by rain, and here we propose a novel method for rain sensing using dual-frequency measurements at 25 and 38GHz from a small-scale Tokyo Institute of Technology (Tokyo Tech) millimeter-wave network. A real-time algorithm is developed for estimating the rain rate from attenuation using both ITU-R relationships and new coefficients that consider the effects of the rain Drop Size Distribution (DSD). The suggested procedure is tested on measured data, and its performance is evaluated. The results show that the proposed algorithm yields estimates that agree very well with rain gauge data.

This paper proposes a novel blind adaptive array scheme with subcarrier transmission power assignment (STPA) for spectrum superposing in cognitive radio networks. The Eigenvector Beamspace Adaptive Array (EBAA) is known to be one of the blind adaptive array algorithms that can suppress inter-system interference without any channel state information (CSI). However, EBAA has difficulty in suppressing interference signals whose Signal to Interference power Ratio (SIR) values at the receiver are around 0dB. With the proposed scheme, the ST intentionally provides a level difference between subcarriers. At the receiver side, the 1st eigenvector of EBAA is applied to the received signals of the subcarrier assigned higher power and the 2nd eigenvector is applied to those assigned lower power. In order to improve interference suppression performance, we incorporate Beamspace Constant Modulus Algorithm (BSCMA) into EBAA (E-BSCMA). Additionally, STPA is effective in reducing the interference experienced by the primary system. Computer simulation results show that the proposed scheme can suppress interference signals received with SIR values of around 0dB while improving operational SIR for the primary system. It can enhance the co-existing region of 2 systems that share a spectrum.

In this paper, the multicell distributed beamforming (MDBF) design problem of suppressing intra-cell interference (InCI) and inter-cell interference (ICI) is studied. To start with, in order to decrease the InCI and ICI caused by a user, we propose a gradient-iteration altruistic algorithm to derive the beamforming vectors. The convergence of the proposed iterative algorithm is proved. Second, a metric function is established to restrict the ICI and maximize cell rate. This function depends on only local channel state information (CSI) and does not need additional CSIs. Moreover, an MDBF algorithm with the metric function is proposed. This proposed algorithm utilizes gradient iteration to maximize the metric function to improve sum rate of the cell. Finally, simulation results demonstrate that the proposed algorithm can achieve higher cell rates while offering more advantages to suppress InCI and ICI than the traditional ones.

This paper presents comprehensive comparisons on the block error rate (BLER) performance of rate-one open-loop (OL) transmit diversity schemes with four antennas for discrete Fourier transform (DFT)-precoded Orthogonal Frequency Division Multiple Access (OFDMA). One candidate scheme employs a quasi-orthogonal (QO) - space-time block code (STBC) in which four-branch minimum mean-square error (MMSE) combining is achieved at the cost of residual inter-code interference (ICI). Another candidate employs a combination of the STBC and selection transmit diversity called time switched transmit diversity (TSTD) (or frequency switched transmit diversity (FSTD)). We apply a turbo frequency domain equalizer (FDE) associated with iterative decision-feedback channel estimation (DFCE) using soft-symbol estimation to reduce channel estimation (CE) error. The turbo FDE includes an ICI canceller to reduce the influence of the residual ICI for the QO-STBC. Based on link-level simulation results, we show that a combination of the STBC and TSTD (or FSTD) is suitable as a four-antenna OL transmit diversity scheme for DFT-precoded OFDMA using the turbo FDE and iterative DFCE.

This paper analyzes the performance of a mobile multihop relay (MMR) system which uses intermediate mobile relay stations (RSs) to increase service coverage area and capacity of a communication system. An analytical framework for an MMR system is introduced, and a scheme for allocating the optimum radio resources to an MMR system is presented. It is very challenging to develop an analytical framework for an MMR system because more than two wireless links should be considered in analyzing the performance of such a system. Here, the joint effect of a finite queue length and an adaptive modulation and coding (AMC) scheme in both a base station (BS) and an RS are considered. The traffic characteristics from BS to RS are analyzed, and a three-dimensional finite-state Markov chain (FSMC) is built for the RS which considers incoming traffic from the BS as well. The RS packet loss rate and the RS average throughput are also derived. Moreover, maximum throughput is achieved by optimizing the amount of radio resources to be allocated to the wireless link between a BS and an RS.

In this paper, we propose an analysis of broadcasting in the IEEE 802.11p MAC protocol. We consider multi-channel operation which is specifically designed for VANET (Vehicular Ad hoc Networks) applications. This protocol supports channel switching; the device alternates between the CCH (Control Channel) and the SCH (Service Channel) during the fixed synchronization interval. It helps vehicles with a single transceiver to access the CCH periodically during which time they acquire or broadcast safety-related messages. Confining the broadcasting opportunity to the deterministic CCH interval entails a non-typical approach to the analysis. Our analysis is carried out considering 1) the time dependency of the system behavior caused by the channel switching, 2) the mutual influence among the vehicles using a multi-dimensional stochastic process, and 3) the generation of messages distributed over the CCH interval. The proposed analysis enables the prediction of the successful delivery ratio and the delay of the broadcast messages. Furthermore, we propose a refinement of the analysis to take account of the effects of hidden nodes on the system performance. The simulation results show that the proposed analysis is quite accurate in describing both the delivery ratio and delay, as well as in reflecting the hidden node effects. The benefits derived from the distributed generation of traffic are also evidenced by the results of experiments.

TV white space (TVWS) brings potential opportunities to relieve the growing spectrum scarcity. Therefore organizations like the FCC have suggested the co-channel deployment of cellular networks (CNs) on condition that a keep-out distance from the protected region of TV receivers is maintained. However the consequent CN interference has not been described. In addition, considering the wide range of TV coverage, it is also inefficient and wasteful not applying the vacant spectra for secondary user (SU) communication by opportunistic access inside the TV coverage zone. In this paper, we first investigate the aggregate interference from CNs outside the protected area to find out how the interference is generated, and then research the available spectrum resource distribution for SUs inside the TV coverage zone under aggregate interference constraints to utilize TVWS more efficiently. Specifically, we model CN in three aspects. A close-form interference probability distribution function (PDF) is proposed. Since the PDF is too complex to analyze, we approximate it as Gaussian and prove the accuracy of our approximation with Kolmogorov-Smirnov test. Then, available spectra maximization is formulated as an optimization problem under both TV and SU receiver outage probability constraints. We find that available spectra demonstrate a volcano-shaped geographical distribution and optimal network-status-aware SU transmit power exists to maximize the spectra. Our analysis reveals the characteristics of interference in TVWS and contributes to the utilization improvement of white space.

This paper presents the effect of transmit diversity on the initial and neighboring cell search time performance and the most appropriate transmit diversity scheme based on system-level simulations employing synchronization signals for the Long Term Evolution (LTE) downlink. The synchronization signals including the primary synchronization signal (PSS) and secondary synchronization signal (SSS) are the first physical channel that a set of user equipment (UE) acquires at the initial radio-link connection. The transmit diversity candidates assumed in the paper are Precoding Vector Switching (PVS), Cyclic Delay Diversity (CDD), Time Switched Transmit Diversity (TSTD), and Frequency Switched Transmit Diversity (FSTD), which are all suitable for simple blind detection at a UE. System-level simulation results show that transmit diversity is effective in improving the detection probabilities of the received PSS timing and PSS sequence in the first step and those of the SSS sequence and radio frame timing in the second step of the cell search process. We also show that PVS achieves fast cell search time performance of less than approximately 20ms at the location probability of 90% regardless of the inter-cell site distance up to 10km. Hence, we conclude that PVS is the best transmit diversity scheme for the synchronization signals from the viewpoint of decreasing the initial and neighboring cell search times.

To achieve accurate wireless-local-area-network (WLAN) positioning, the directivity and influence of multipath fading on the power absorption by the user are clarified experimentally. Based on the results, a general model of the power absorption by the user is devised. The parameters of the model are estimated using maximum-likelihood estimation (MLE) and the magnetic sensor built into modern smartphones. The proposed method compensates the power absorption and the influence of multipath fading. According to experimental evaluations, the root-mean-square error (RMSE) of the proposed method is 34% lower than that of the conventional one. Namely, RMSE of the proposed method is 1.94m in a room.

Due to low signal-to-carrier ratio and high dynamic, the frequency deviation affects the bit synchronization in GNSS receiver. This paper proposes a balance differential coherent bit synchronization algorithm, which uses the differential coherent method to eliminate the influence of the frequency deviation. By enlarging the differential distance, the proposed algorithm achieves higher bit synchronization rates. Combining two complementary differential coherent parts, the proposed algorithm avoids the unbalance problem and the attenuation of accumulation. Furthermore, a general architecture is presented to reduce the system complexity. Experimental results show that the proposed algorithm improves the sensitivity of bit synchronization by 3∼7dB compared with the previous method.