Software-defined networking (SDN) decouples the control and forwarding of network devices, providing benefits such as simplified control. However, due to cost constraints and other factors, SDN is difficult to fully deploy. It has been proposed that SDN devices can be incrementally deployed in a traditional IP network, i.e., hybrid SDN, to provide partial SDN benefits. Studies have shown that better traffic engineering performance can be achieved by modifying the coverage and placement of SDN devices in hybrid SDN, because they can influence the behavior of legacy switches through certain strategies. However, it is difficult to develop and execute a traffic engineering strategy in hybrid SDN. This article proposes a routing algorithm to achieve approximate load balancing, which minimizes the maximum link utilization by using the optimal solution of linear programming and merging the minimum split traffic flows. A multipath forwarding mechanism under the same problem is designed to optimize transmission time. Experiments show that our algorithm has certain advantages in link utilization and transmission time compared to traditional distributed routing algorithms like OSPF and some hybrid SDN routing mechanisms. Furthermore, our algorithm can approximate the control effect of full SDN when the deployment rate of SDN devices is 40%.

Cloud-based Global Navigation Satellite Systems (CB-GNSS) positioning architecture that offloads part of GNSS positioning computation to cloud/edge infrastructure has been studied as an architecture that adds valued functions via the network. The merits of CB-GNSS positioning are that it can take advantage of the abundant computing resources on the cloud/edge to add unique functions to the positioning calculation and reduce the cost of GNSS receiver terminals. An issue in GNSS positioning is the degradation in positioning accuracy in unideal reception environments where open space is limited and some satellite signals are blocked. To resolve this issue, we propose a satellite selection algorithm that effectively removes the multipath components of blocked satellite signals, which are the main cause of drop in positioning accuracy. We build a Proof of Concept (PoC) test environment of CB-GNSS positioning architecture implementing the proposed satellite selection algorithm and conduct experiments to verify its positioning performance in unideal static and dynamic conditions. For static long-term positioning in a multipath signal reception environment, we found that CB-GNSS positioning with the proposed algorithm enables a low-end GNSS receiver terminal to match the positioning performance comparable to high-end GNSS receiver terminals in terms of the FIX rate. In an autonomous tractor driving experiment on a farm road crossing a windbreak, we succeeded in controlling the tractor's autonomous movement by maintaining highly precise positioning even in the windbreak. These results indicates that the proposed satellite selection algorithm achieves high positioning performance even in poor satellite signal reception environments.

With multiple network interfaces are being widely equipped in modern mobile devices, the Multipath TCP (MPTCP) is increasingly becoming the preferred transport technique since it can uses multiple network interfaces simultaneously to spread the data across multiple network paths for throughput improvement. However, the MPTCP performance can be seriously affected by the use of a poor-performing path in multipath transmission, especially in the presence of network attacks, in which an MPTCP path would abrupt and frequent become underperforming caused by attacks. In this paper, we propose a multi-expert Learning-based MPTCP variant, called MPTCP-meLearning, to enhance MPTCP performance robustness against network attacks. MPTCP-meLearning introduces a new kind of predictor to possibly achieve better quality prediction accuracy for each of multiple paths, by leveraging a group of representative formula-based predictors. MPTCP-meLearning includes a novel mechanism to intelligently manage multiple paths in order to possibly mitigate the out-of-order reception and receive buffer blocking problems. Experimental results demonstrate that MPTCP-meLearning can achieve better transmission performance and quality of service than the baseline MPTCP scheme.

This paper proposes time division multiplexing (TDM) based reference signal (RS) multiplexing for faster-than-Nyquist (FTN) signaling using orthogonal frequency division multiplexing (OFDM). We also propose a subframe structure in which a cyclic prefix (CP) is appended to only the TDM based RS block and the first FTN symbol to achieve accurate estimation of the channel response in a multipath fading channel with low CP overhead. Computer simulation results show that the loss in the required average received SNR satisfying the average block error rate (BLER) of 10-2 using the proposed TDM based RS multiplexing from that with ideal channel estimation is suppressed to within approximately 1.2dB and 1.7dB for QPSK and 16QAM, respectively. This is compared to when the improvement ratio of the spectral efficiency from CP-OFDM is 1.31 with the rate-1/2 turbo code. We conclude that the TDM based RS multiplexing with the associated CP multiplexing is effective in achieving accurate channel estimation for FTN signaling using OFDM.

In this paper, we address the problem of detector design in severely frequency-selective channels for spatial multiplexing systems that adopt filter bank multicarrier based on offset quadrature amplitude modulation (FBMC/OQAM) as the communication waveforms. We consider decision feedback equalizers (DFEs) that use multiple feedback filters to jointly cancel the post-cursor components of inter-symbol interference, inter-antenna interference, and, in some configuration, inter-subchannel interference. By exploiting the special structures of the correlation matrix and the staggered property of the FBMC/OQAM signals, we obtain an efficient method of computing the DFE coefficients that requires a smaller number of multiplications than the linear equalizer (LE) and conventional DFE do. The simulation results show that the proposed detectors considerably outperform the LE and conventional DFE at moderate-to-high signal-to-noise ratios.

The carrier-phase multipath effect can seriously affect the accuracy of GPS-based positioning in static short baseline applications. Although several kinds of methods based on time domain and spatial domain techniques have been proposed to mitigate this error, they are still limited by the accuracy of the multipath model and the effectiveness of the correction strategy. After analyzing the existing methods, a new method based on adaptive thresholding wavelet packet transform (AW) and time domain bootstrap spatial domain search strategy (TB) is presented (AWTB). Taking advantage of adaptive thresholding wavelet packet transform, we enhance the precision of the correction model and the efficiency of the extraction method. In addition, by adopting the proposed time domain bootstrap spatial domain strategy, the accuracy and efficiency of subsequent multipath correction are improved significantly. Specifically, after applying the adaptive thresholding wavelet packet method, the mean improvement rate in the RMS values of the single-difference L1 residuals is about 27.93% compared with the original results. Furthermore, after applying the proposed AWTB method, experiments show that the 3D positioning precision is improved by about 38.51% compared with the original results. Even compared with the method based on stationary wavelet transform (SWT), and the method based on wavelet packets denoising (WPD), the 3D precision is improved by about 26.94% over the SWT method and about 22.96% over the WPD method, respectively. It is worth noting that, although the mean time consumption of the proposed algorithm is larger than the original method, the increased time consumption is not a serious burden for overall performance.

As a key technology for 5G and beyond, Multi-User Multi-Input Multi-Output (MU-MIMO) can achieve Gbps downlink rate by allowing concurrent transmission from one Access Point (AP) to multiple users. However, the huge overhead of full CSI feedback may overwhelm the gain yielded by beamforming. Although there have been many works on compress CSI to reduce the feedback overhead, the performance of beamforming may decrease because the accuracy of channel state degrades. To address the tradeoff between feedback overhead and accuracy, we present a two-stage Multipath Profile based Feedback protocol (MPF). In the first stage, compared with CSI feedback, the channel state is represented by multipath profile which has a smaller size but is accurate enough for user selection. Meanwhile, we propose an implicit polling scheme to decrease the feedback further. In the second stage, only the selected users send their CSI information to the AP to guarantee the low overhead and accuracy of steering matrix calculation. We implement and evaluate MPF with USRP N210. Experiments show that MPF can outperform alternative schemes in a variety of radio environments.

The conventional universal filtered-DFT-spread-OFDM (UF-DFTs-OFDM) can drastically improve the out-of-band emission (OOBE) caused by the discontinuity between symbols in the conventional cyclic prefix-based DFTs-OFDM (CP-DFTs-OFDM). However, the UF-DFTs-OFDM degrades the communication quality in a long-delay multipath fading environment due to the frequency-domain ripple derived from the long transition time of the low pass filter (LPF) corresponding to the guard interval (GI). In this paper, we propose an enhanced UF-DFTs-OFDM (eUF-DFTs-OFDM) that achieves significantly low OOBE and high communication quality even in a long-delay multipath fading environment. The eUF-DFTs-OFDM applies an LPF with quite short length in combination with the zero padding (ZP) or the CP process. Then, the characteristics of the OOBE, peak-to-average power ratio (PAPR), and block error rate (BLER) are evaluated by computer simulation with the LTE uplink parameters. The result confirms that the eUF-DFTs-OFDM can improve the OOBE by 22.5dB at the channel-edge compared to the CP-DFTs-OFDM, and also improve the ES/N0 to achieve BLER =10-3 by about 2.5dB for QPSK and 16QAM compared to the UF-DFTs-OFDM. For 64QAM, the proposed eUF-DFTs-ODFDM can eliminate the error floor of the UF-DFTs-OFDM. These results indicate that the proposed eUF-DFTs-OFDM can significantly reduce the OOBE while maintaining the same level of communication quality as the CP-DFTs-OFDM even in long-delay multipath environment.

When considering the deployment of a radio communications network, the study of multipath interference and its impact on the quality of signal reception is of the outmost importance in order to meet the necessary performance requirements. This work considers specifically the case of the lunar surface as the mission scenario for a community of autonomous mobile exploration robots, which communicate through a radiofrequency network to accomplish their mission. In this application, the low height of the mobile robots makes the influence of multipath interference effects on the performance of the radio communication channel relevant. However, no specific information about lunar soil reflection coefficients characteristics is available for radiofrequency communication bands. This work reviews the literature on the electrical parameter of Lunar soil. From this base, the reflection coefficients are estimated for the assumed radio profile in different communications frequency bands. Finally, the results obtained are discussed.

Filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) is considered an alternative to conventional orthogonal frequency division multiplexing (OFDM) to meet the various requirements proposed by future communication networks. Among the different perspectives on the merits of FBMC-OQAM and OFDM, a straightforward metric is the bit error probability (BEP). This paper presents a general analytical framework for BEP evaluation that is applicable to FBMC-OQAM and OFDM systems in both Rayleigh and Rician multipath fading channels. Explicit BEP expressions are derived for Gray-coded pulse amplitude modulation (PAM) and square quadrature amplitude modulation (QAM) signals with arbitrary constellation sizes. The theoretical analysis results show excellent agreement with the numerical simulation results in different channel scenarios.

Softwarized networks are expected to be utilized as a core network for the 5th Generation (5G) mobile services. For the mobile core network architecture, service chaining is expected to be utilized for dynamically steering traffic across multiple network functions. In this paper, for dynamic multipath service chaining, we propose a greedy-based VNF placement algorithm. This method can provide multipath service chaining so as to utilize the node resources such as CPU effectively while decreasing the cost about bandwidth and transmission delay. The proposed algorithm consists of four difference algorithms, and VNFs are placed appropriately with those algorithm. Our proposed algorithm obtains near optimal solution for the formulated optimization problem with a greedy algorithm, and hence multipath service chains can be provided dynamically. We evaluate the performance of our proposed method with simulation and compare its performance with the performances of other methods. In numerical examples, it is shown that our proposed algorithm can provide multipath service chains appropriately so as to utilize the limited amount of node resources effectively. Moreover, it is shown that our proposed algorithm is effective for providing service chaining dynamically in large-scale network.

The low-altitude target detection remains a difficult problem in MIMO radar. In this paper, we propose a novel adaptive two-step Bayesian generalized likelihood ratio test (TB-GLRT) detection algorithm for low-altitude target detection. By defining the compound channel scattering coefficient and applying the K distributed clutter model, the signal models for different radars in low-altitude environment are established. Then, aiming at the problem that the integrals are too complex to yield a closed-form Neyman-Pearson detector, we assume prior knowledge of the channel scattering coefficient and clutter to design an adaptive two-step Bayesian GLRT algorithm for low-altitude target detection. Monte Carlo simulation results verify that the proposed detector has better performance than the square law detector, GLRT detector or Bayesian GLRT detector in low-altitude environment. With the TB-GLRT detector, the maximum detection probability can reach 70% when SNR=0dB and ν=1. Simulations also verify that the multipath effect shows positive influence on detection when SNR<5dB, and when SNR>10dB, the multipath effect shows negative influence on detection. When SNR>0dB, the MIMO radar, which keeps a detection probability over 70% with the proposed algorithm, has the best detection performance. Besides, the detection performance gets improved with the decrease of sea clutter fluctuation level.

Recently, application demands placed on the network have become more multifaceted. Highly functional application-to-application communication services such as bandwidth aggregation, fault tolerant communication, and delay/disruption tolerant networking (DTN) were developed independently in the network layer, the transport layer, and the application layer. As a result, protocol layering has become complicated. This paper proposes to insert Layer-5 (L5) between the application layer and the transport layer to separate communication policies and communication mechanisms to make protocol layering clearer. The transport layer (L4) provides end-to-end communication mechanisms such as reliable byte stream while L5 realizes communication policies such as bandwidth aggregation by combining the communication mechanisms in L4. This paper proposes five types of L5-paths as communication policies: (1) the L5 bundled path for bandwidth aggregation or fault tolerant communication, (2) the L5 spatially-spliced path for communication with middleboxes, (3) the L5 temporally-spliced path for DTN, (4) the L5 spliced-bundled path, and (5) the L5 bundled over spatially-spliced path. An application can select and use an appropriate L5-path depending on the network circumstances through a common API. A prototype of L5 is implemented in the Linux user space as a library to make deployment and maintenance easier. An evaluation shows that establishment time of L5-paths is short enough and performance of L5-paths is comparable or superior to existing technologies.

A triangular decomposition-based multipath super-resolution method is proposed to improve the range resolution of small unmanned aerial vehicle (UAV) radar altimeters that use a single channel with continuous direct spread waveform. In the engineering applications of small UAV radar altimeter, multipath scenarios are quite common. When the conventional matched filtering process is used under these environments, it is difficult to identify multiple targets in the same range cell due to the overlap between echoes. To improve the performance, we decompose the overlapped peaks yielded by matched filtering into a series of basic triangular waveforms to identify various targets with different time-shifted correlations of the pseudo-noise (PN) sequence. Shifting the time scale enables targets in the same range resolution unit to be identified. Both theoretical analysis and experiments show that the range resolution can be improved significantly, as it outperforms traditional matched filtering processes.

In this paper, MWAN (Mobile Wireless Ad hoc Networks with internet connection) is considered, which is a solution for many tasks owing to its ease of use, and practicality. Recently, MWAN is required to support large data like multimedia data transfer and it is transferred through several relay nodes. There are 2 problems that cause difficulties for large data transfer through a mobile network. First one is rerouting delay by handoff and second one is network congestion caused by handoff. Also, faulty data transfer caused by handoff delay makes extra load and causes some problems for MWAN. To solve these problems and get network reliability, we propose a new multipath routing scheme that can provide solution for seamless connection while handoff. In the proposed scheme, our MWAN can support multiple paths for data transfer, maintain end-to-end connection while handoff and get new route quickly. The performance of the proposed scheme is evaluated and compared with other multipath routing scheme to show the improvement.

This paper proposes an effective continuous super-resolution (CSR) algorithm for the multipath channel estimation. By designing a preamble including up-chirp and down-chirp symbols, the Doppler shift and multipath delay are estimated jointly by using convex programming. Simulation results show that the proposed CSR can achieve better detection probability of the number of multipaths than the eigenvalue based methods. Moreover, compared with conventional super-resolution techniques, such as MUSIC and ESPRIT methods, the proposed CSR algorithm demonstrates its advantage in root mean square error of the Doppler shift and multipath delay, especially for the closely located paths within low SNR.

In this paper, a hardware efficient design methodology for a configurable-point multiple-stream pipeline FFT processor is presented. We first compared the memory and arithmetic components of different pipeline FFT architectures, and obtained the conclusion that MDF architecture is more hardware efficient than MDC for the overall processor. Then, in order to reduce the computational complexity, a binary-tree representation was adopted to analyze the decomposition algorithm. Consequently, the coefficient multiplications are minimized among all the decomposition probabilities. In addition, an efficient output reorder circuit was designed for the multiple-stream architecture. An 128∼2048 point 4-stream FFT processor in LTE system was designed in SMIC 55nm technology for evaluation. It owns 1.09mm2 core area with 82.6mW power consumption at 122.88MHz clock frequency.

Mutipath matching pursuit (MMP) is a new reconstruction algorithm based on compressed sensing (CS). In this letter, we applied the MMP algorithm to channel estimation in orthogonal frequency division multiplexing (OFDM) communication systems, and then proposed an improved MMP algorithm. The improved method adjusted the number of children generated by candidates. It can greatly reduce the complexity. The simulation results demonstrate that the improved method can reduce the running time under the premise of guaranteeing the performance of channel estimation.

This paper proposes a technique for efficient standing multipath mitigation of geostationary earth orbit (GEO) satellites. The performance of traditional filtering methods for GEO multipath errors can be effectively improved by using carrier frequency variation approach. Conventional multipath mitigation methods do not pay much attention to the GEO satellite multipath effects, and they are less effective due to the non-zero average characteristics of GEO multipath errors for short epochs. By varying carrier frequency, the multipath error average becomes approaching zero in short epochs due to the faster multipath carrier phase variation. Therefore, it could enhance the traditional filtering method performance on the multipath signals. By varying the carrier frequency or the carrier phase offset, the average multipath error will approach zero as a result of the frequent multipath carrier phase variations. This method aims to explore the potential for signal pattern design while improving the performance of current satellite navigation systems. The results show that the root mean square error (RMSE) for pseudo-range multipath errors of the proposed approach improves about 0.3m with a frequency variation range of 15MHz.

A novel virtual sensors-based positioning method has been presented in this paper, which can make use of both direct paths and indirect paths. By integrating the virtual sensor idea and Bayesian state and observation framework, this method models the indirect paths corresponding to persistent virtual sensors as virtual direct paths and further reformulates the wireless positioning problem as the maximum likelihood estimation of both the mobile terminal's positions and the persistent virtual sensors' positions. Then the method adopts the EM (Expectation Maximization) and the particle filtering schemes to estimate the virtual sensors' positions and finally exploits not only the direct paths' measurements but also the indirect paths' measurements to realize the mobile terminal's positions estimation, thus achieving better positioning performance. Simulation results demonstrate the effectiveness of the proposed method.