In this paper, we report an experimental and numerical analysis of ultrahigh-speed coherent Nyquist pulse transmission. First, we describe a low-nonlinearity dispersion compensator for ultrahigh-speed coherent Nyquist pulse transmission; it is composed of a chirped fiber Bragg grating (CFBG) and a liquid crystal on silicon (LCoS) device. By adopting CFBG instead of inverse dispersion fiber, the nonlinearity in a 160km transmission line was more than halved. Furthermore, by eliminating the group delay fluctuation of the CFBG with an LCoS device, the residual group delay was reduced to as low as 1.42ps over an 11nm bandwidth. Then, by using the transmission line with the newly constructed low-nonlinearity dispersion compensator, we succeeded in improving the BER performance of single-channel 15.3Tbit/s-160km transmission by one-third compared with that of a conventional dispersion-managed transmission line and obtained a spectral efficiency of 8.7bit/s/Hz. Furthermore, we numerically analyzed the BER performance of its Nyquist pulse transmission. The numerical results showed that the nonlinear impairment in the transmission line is the main factor limiting the transmission performance in a coherent Nyquist pulse transmission, which becomes more significant at higher baud rates.

In order to further reduce the transmission rate of multi-channel satellite broadcast signals, whose carrier-to-noise ratio (CNR fluctuates due to rainfall attenuation, we propose a novel digitized radio-over-fiber (DRoF) -based optical re-transmission system based on adaptive combination compression for ultra-high definition (UHD) broadcasting satellite (BS)/communications satellite (CS) broadcast signals. The proposed system reduces the optical re-transmission rate of BS/CS signals as much as possible while handling input CNR fluctuations. Therefore, the transmission rate of communication signals in time-division multiplexing (TDM) transmission is ensured, and network sharing of communication signals and broadcast signals via passive optical network (PON) is realized. Based on the ITU-R P.618-13 prediction model, an experimental evaluation is performed using estimates of the long-term statistics of attenuation due to rainfall. The attenuation is evaluated as a percentage of the time that long-term re-transmission service is available. It is shown that the proposed system is able to accommodate a wide range of rainfall attenuation and achieve a 99.988% time percentage for the duration of service provision. In order to show the rate reduction effect of the proposed system, the quantization bit reduction effect as a function of the input CNR, which depends on rainfall attenuation, is experimentally confirmed. Experiments show that service operation time of 99.978% can be achieved by 3-bit transmission. This means a 62.5% reduction in transmission rate is realized compared to conventional fixed quantization. Furthermore, the average quantization bit number in our system for service operation times is 3.000, indicating that most service operation times are covered by just 3-bit transmission.

To accommodate an increasing amount of traffic efficiently, elastic optical networks (EON) that can use optical spectrum resources flexibly have been studied. We implement multi-path routing in case we cannot allocate the spectrum with single-path routing. However, multi-path routing requires more guard bands to avoid interference between two adjacent optical paths when compared with single-path routing in EON. A multi-path routing algorithm with traffic grooming technology has been proposed. The researchers assumed that a uniform modulation level was adopted, and so they did not consider the impact of path length on the resources needed. In this paper, we propose a multi-path routing method with traffic grooming considering path lengths. Our proposed method establishes an optical multi-path considering path length, fiber utilization, and the use of traffic grooming. Simulations show we can decrease the call-blocking probability by approximately 24.8% in NSFNET. We also demonstrate the effectiveness of traffic grooming and the improvement in the utilization ratio of optical spectrum resources.

Real-time applications are becoming more and more popular, and due to the demand for more compact and portable user devices, offloading terminal processes to edge servers is being considered. Moreover, it is necessary to process packets with low latency on edge servers, which are often virtualized for operability. When trying to achieve low-latency networking, the increase in server power consumption due to performance tuning and busy polling for fast packet receiving becomes a problem. Thus, we design and implement a low-latency and energy-efficient networking system, energy-efficient kernel busy poll (EE-KBP), which meets four requirements: (A) low latency in the order of microseconds for packet forwarding in a virtual server, (B) lower power consumption than existing solutions, (C) no need for application modification, and (D) no need for software redevelopment with each kernel security update. EE-KBP sets a polling thread in a Linux kernel that receives packets with low latency in polling mode while packets are arriving, and when no packets are arriving, it sleeps and lowers the CPU operating frequency. Evaluations indicate that EE-KBP achieves microsecond-order low-latency networking under most traffic conditions, and 1.4× to 3.1× higher throughput with lower power consumption than NAPI used in a Linux kernel.

The integration of social networking concepts into the Internet of Things has led to the Social Internet of Things (SIoT) paradigm, and trust evaluation is essential to secure interaction in SIoT. In SIoT, when resource-constrained nodes respond to unexpected malicious services and malicious recommendations, the trust assessment is prone to be inaccurate, and the existing architecture has the risk of privacy leakage. An edge-cloud collaborative trust evaluation architecture in SIoT is proposed in this paper. Utilize the resource advantages of the cloud and the edge to complete the trust assessment task collaboratively. An evaluation algorithm of relationship closeness between nodes is designed to evaluate neighbor nodes' reliability in SIoT. A trust computing algorithm with enhanced sensitivity is proposed, considering the fluctuation of trust value and the conflict between trust indicators to enhance the sensitivity of identifying malicious behaviors. Simulation results show that compared with traditional methods, the proposed trust evaluation method can effectively improve the success rate of interaction and reduce the false detection rate when dealing with malicious services and malicious recommendations.

This paper investigates the joint problem of user association and spectrum allocation in satellite-terrestrial integrated networks (STINs), where a low earth orbit (LEO) satellite access network cooperating with terrestrial networks constitutes a heterogeneous network, which is beneficial in terms of both providing seamless coverage as well as improving the backhaul capacity for the dense network scenario. However, the orbital movement of satellites results in the dynamic change of accessible satellites and the backhaul capacities. Moreover, spectrum sharing may be faced with severe co-channel interferences (CCIs) caused by overlapping coverage of multiple access points (APs). This paper aims to maximize the total sum rate considering the influences of the dynamic feature of STIN, backhaul capacity limitation and interference management. The optimization problem is then decomposed into two subproblems: resource allocation for terrestrial communications and satellite communications, which are both solved by matching algorithms. Finally, simulation results show the effectiveness of our proposed scheme in terms of STIN's sum rate and spectrum efficiency.

In this paper, we propose applying our previously reported adaptive peak-to-average power ratio (PAPR) reduction method using null space in a multiple-input multiple-output (MIMO) channel for orthogonal frequency division multiplexing (OFDM) signals to the downlink MIMO amplify-and-forward (AF) relaying transmission. Assuming MIMO-OFDM transmission, mitigating its high PAPR not only at the base station (BS) but also at the relay station (RS) transmitters is essential to achieve sufficient coverage enhancement from the RSs by minimizing the transmission power backoff levels at the nonlinear power amplifier. In this study, we assume an AF-type RS with multiple antennas. In the proposed method, the BS suppresses the PAPR of the transmitted signal through adaptive PAPR reduction utilizing the null space of the integrated overall MIMO channel that combines the channel between the BS and RS and the channel between the RS and a set of user equipment (UE). However, the PAPR of the received signal at each RS antenna is increased again due to the MIMO channel between the BS and RS. The proposed method reduces this increased PAPR at the AF-type RS transmitter by PAPR reduction processing that utilizes the null space in the MIMO channel between the RS and UE. Since the in-band PAPR reduction signal added at the RS transmitter is transmitted only in the null space of the MIMO channel between the RS and UE, interference at the UE receiver is mitigated. Computer simulation results show that the proposed method significantly improves the PAPR-vs.-throughput performance compared to that for the conventional one thanks to the reduced interference levels from the PAPR reduction signal observed at the UE receiver.

This paper proposes a novel interference cancellation technique that prevents radio receivers from degrading due to periodic interference signals caused by electromagnetic waves emitted from high power circuits. The proposed technique cancels periodic interference signals in the frequency domain, even if the periodic interference signals drift in the time domain. We propose a drift estimation based on a super resolution technique such as ESPRIT. Moreover, we propose a sequential drift estimation to enhance the drift estimation performance. The proposed technique employs a linear filter based on the minimum mean square error criterion with assistance of the estimated drifts for the interference cancellation. The performance of the proposed technique is confirmed by computer simulation. The proposed technique achieves a gain of more than 40dB at the higher frequency part in the band. The proposed canceler achieves such superior performance, if the parameter sets are carefully selected. The proposed sequential drift estimation relaxes the parameter constraints, and enables the proposed cancellation to achieve the performance upper bound.

In a previous study, we proposed a new method based on copula theory to evaluate the detection performance of distributed-processing multistatic radar systems, in which the dependence of local decisions was modeled by a Gaussian copula with linear dependence and no tail dependence. However, we also noted that one main limitation of the study was the lack of investigations on the tail-dependence and nonlinear dependence among local detectors' inputs whose densities have long tails and are often used to model clutter and wanted signals in high-resolution radars. In this work, we attempt to overcome this shortcoming by extending the application of the proposed method to several types of multivariate copula-based dependence models to clarify the effects of tail-dependence and different dependence models on the system detection performance in detail. Our careful analysis provides two interesting and important clarifications: first, the detection performance degrades significantly with tail dependence; and second, this degradation mainly originates from the upper tail dependence, while the lower tail and nonlinear dependence unexpectedly improve the system performance.