Performance Evaluation of Variable Bandwidth Channel Allocation Scheme in Multiple Subcarrier Multiple Access

Multiple Subcarrier Multiple Access (MSMA) enables concurrent sensor data streamings from multiple wireless and batteryless sensors using the principle of subcarrier backscatter used extensively in passive RFID. Since the interference cancellation performance of MSMA depends on the Signal to Interference plus Noise Ratio of each subcarrier, the choice of channel allocation scheme is essential. Since the channel allocation is a combinatorial problem, obtaining the true optimal allocation requires a vast amount of examinations which is impracticable in a system where we have tens of sensor RF tags. It is particularly true when we have variable distance and variable bandwidth sensor RF tags. This paper proposes a channel allocation scheme in the variable distance and variable bandwidth MSMA system based on a newly introduced performance index, total contamination power, to prioritize indecision cases. The performance of the proposal is evaluated with existing methods in terms of average communication capacity and system fairness using MATLAB Monte Carlo simulation to reveal its advantage. The accuracy of the simulation is also verified with the result obtained from the brute force method

Concurrent Backscatter Streaming from Batteryless and Wireless Sensor Tags with Multiple Subcarrier Multiple Access

This paper proposes a novel multiple access method that enables concurrent sensor data streaming from multiple batteryless, wireless sensor tags. The access method is a pseudo-FDMA scheme based on the subcarrier backscatter communication principle, which is widely employed in passive RFID and radar systems. Concurrency is realized by assigning a dedicated subcarrier to each sensor tag and letting all sensor tags backscatter simultaneously. Because of the nature of the subcarrier, which is produced by constant rate switching of antenna impedance without any channel filter in the sensor tag, the tag-to-reader link always exhibits harmonics. Thus, it is important to reject harmonics when concurrent data streaming is required. This paper proposes a harmonics rejecting receiver to allow simultaneous multiple subcarrier usage. This paper particularly focuses on analog sensor data streaming which minimizes the functional requirements on the sensor tag and frequency bandwidth. The harmonics rejection receiver is realized by carefully handling group delay and phase delay of the subcarrier envelope and the carrier signal to accurately produce replica of the harmonics by introducing Hilbert and inverse Hilbert transformations. A numerical simulator with Simulink and a hardware implementation with USRP and LabVIEW have been developed. Simulations and experiments reveal that even if the CIR before harmonics rejection is 0dB, the proposed receiver recovers the original sensor data with over 0.98 cross-correlation

RSSI系列類似性比較による発信源の近接関係推定における離散フーリエ変換を用いた距離関数の適用効果

ユークリッド距離やDTWなどの距離関数は時系列データ分析で一般的に使われているが，ノイズに弱いという欠点がある．これに対し，ノイズ耐性のある離散フーリエ変換を用いた距離関数が提案されている．本論文は伝搬環境の影響を受けやすいRSSI時系列データから発信源の近接関係を推定する問題に対し，離散フーリエ変換を用いた距離関数の適用効果を定量的に評価した．We use distance function for proximity estimation of transmission source in order to estimate objects location without distance measurement. The distance function needs tolerance to fluctuation of RSSI to estimate proximity accurately. This letter reports result of comparing noise tolerance of distance function using discrete Fourier transform with general distance function

普及型ソフトウェア無線を用いたモノパルススイッチングによる電波到来方向検知

著者らは無線通信機能がある携帯端末と複数の受信専用普及型ソフトウェア無線装置(SDR)を組み合わせることで通信相手が発する電波の到来方向を検知するシステムの実現を目指している．搬送波の位相情報を利用し到来方向を検知するためには，複数アンテナで電波を受信し，各アンテナと位相差検知回路の経路上の周波数変換器のクロック及び位相が同一である必要がある．しかし，普及型SDR装置を複数用いる場合，各SDR装置で生じる位相オフセットをキャンセルせねばならない．更に到来方向検知精度の劣化の原因となるマルチパスの対策も講じる必要がある．本論文では，2入力2出力スイッチをアンテナとSDR装置の間に挿入し，入力信号を切り替えて簡単な信号処理で位相オフセットをキャンセルできるモノパルススイッチングを提案し，その有効性を実験で検証し，到来方向検知誤差が3.0°以内で動作することを確認した．マルチパスの対策としては，複素モノパルスとモノパルススイッチングを組み合わせた複素モノパルススイッチングを提案する．複素モノパルス比の複素平面上の位置を確認することで，マルチパスの影響が大きいタイミングを検知・回避できることを実験により示した．The authors target the realization of AoA estimation system by plugging in two commercial off the shelf (COTS) software defined radio (SDR) modules on a mobile terminal. The simultaneous usage of two COTS SDRs suffers from the phase offset occurred in each SDR even after we synchronize the clock. To cancel the phase offset, we propose Monopulse Switching, which produces two sets of phase measurements with a double pole and double throw (DPDT) switch implemented between each antenna and SDR module, in this paper. A simple signal processing of the two sets IQ data cancels the phase offset. The AoA estimation accuracy of Monopulse Switching is evaluated both in wired and wireless environments to reveal we can achieve 3.0 degree accuracy. We also quantify the AoA accuracy degradation stemming from the inevitable multiphase and propose to apply a complex monopulse combined with Monopulse Switching to detect and eliminate the degraded measurements

USE OF RFID AT LARGE-SCALE EVENTS

Radio Frequency Identification (RFID) devices and related technologies have received a great deal of attention for their ability to perform non-contact object identification. Systems incorporating RFID have been evaluated from a variety of perspectives. The authors constructed a networked RFID system to support event management at NetWorld+Interop 2004 Tokyo, an event that received 150,000 visitors. The system used multiple RFID readers installed at the venue and RFID tags carried by each visitor to provide a platform for running various management and visitor support applications. This paper presents the results of this field trial of RFID readability rates. It further addresses the applicability of RFID systems to visitor management, a problematic aspect of large-scale events

Normalization of Radio Feature for Online Learning for Identification in Cognitive Radio

The identification of the radio access technology (RAT) of the primary user by secondary users is important to avoid interference for spectrum-sharing techniques using cognitive radio (CR). RATs have become more diversified with the introduction of various services that use wireless communication. Therefore, it is desirable that a RAT identification system, which can easily cope with the diversification of RATs, is applied to CR. The purpose of this study is to use online learning to identify multiple RATs in the same frequency band. To improve the accuracy of identifying RATs with similar features, we evaluate a normalization of radio feature method proposed in our previous research for the features extracted from the signal's spectrogram. We evaluate the RAT classifier created using the proposed method by calculating the curve of receiver operating characteristics (ROC) and the identification accuracy. The results for the ROC curve show that the proposed method is effective for several supervised learning methods. Moreover, the results for the identification accuracy show that the proposed method improves the identification performance compared to the identification accuracy of conventional methods

Active RFID Attached Object Clustering Method with New Evaluation Criterion for Finding Lost Objects

An active radio frequency identification (RFID) tag that can communicate with smartphones using Bluetooth low energy technology has recently received widespread attention. We have studied a novel approach to finding lost objects using active RFID. We hypothesize that users can deduce the location of a lost object from information about surrounding objects in an environment where RFID tags are attached to all personal belongings. To help find lost objects from the proximity between RFID tags, the system calculates the proximity between pairs of RFID tags from the RSSI series and estimates the groups of objects in the neighborhood. We developed a method for calculating the proximity of the lost object to those around it using a distance function between RSSI series and estimating the group by hierarchical clustering. There is no method to evaluate whether a combination is suitable for application purposes directly. Presently, different combinations of distance functions and clustering algorithms yield different clustering results. Thus, we propose the number of nearest neighbor candidates (NNNC) as the criterion to evaluate the clustering results. The simulation results show that the NNNC is an appropriate evaluation criterion for our system because it is able to exhaustively evaluate the combination of distance functions and clustering algorithms