Mamiko Inamori

Bio: Mamiko Inamori is an academic researcher from Tokai University. The author has contributed to research in topics: Orthogonal frequency-division multiplexing & Bit error rate. The author has an hindex of 10, co-authored 95 publications receiving 496 citations. Previous affiliations of Mamiko Inamori include Keio University.

Spectrum Sensing Algorithms via Finite Random Matrices

Abstract: We address the Primary User (PU) detection (spectrum sensing) problem, relevant to cognitive radio, from a finite random matrix theoretical (RMT) perspective. Specifically, we employ recently-derived closed-form and exact expressions for the distribution of the standard condition number (SCN) of uncorrelated and semi-correlated random dual central Wishart matrices of finite sizes in the design Hypothesis-Testing algorithms to detect the presence of PU signals. In particular, two algorithms are designed, with basis on the SCN distribution in the absence (H0) and in the presence (H1) of PU signals, respectively. Due to an inherent property of the SCN's, the H0 test requires no estimation of SNR or any other information on the PU signal, while the H1 test requires SNR only. Further attractive advantages of the new techniques are: a) due to the accuracy of the finite SCN distributions, superior performance is achieved under a finite number of samples, compared to asymptotic RMT-based alternatives; b) since expressions to model the SCN statistics both in the absence and presence of PU signal are used, the statistics of the spectrum sensing problem in question is completely characterized; and c) as a consequence of a) and b), accurate and simple analytical expressions for the receiver operating characteristic (ROC) - both in terms of the probability of detection as a function of the probability of false alarm (PD versus PF) and in terms of the probability of acquisition as a function of the probability of miss detection (PA versus PM) - are yielded. It is also shown that the proposed finite RMT-based algorithms outperform all similar alternatives currently known in the literature, at a substantially lower complexity. In the process, several new results on the distributions of eigenvalues and SCNs of random Wishart Matrices are offered, including a closed-form of the Marchenko-Pastur's Cumulative Density Function (CDF) and extensions of the latter, as well as variations of asymptotic the distributions of extreme eigenvalues (Tracy-Widom) and their ratio (Tracy-Widom-Curtiss), which are simpler than those obtained with the "spiked population model".

IQ imbalance compensation scheme in the presence of frequency offset and dynamic DC offset for a direct conversion receiver

Abstract: A direct conversion architecture reduces the cost and power consumption of a receiver. However, a direct conversion receiver may suffer from direct current (DC) offset, frequency offset, and IQ imbalance. This paper presents an IQ imbalance estimation scheme for orthogonal frequency division multiplexing (OFDM) direct conversion receivers. The proposed IQ imbalance estimation scheme operates in the presence of dynamic DC offset and frequency offset. The proposed scheme calculates IQ imbalance from a simple equation. It employs the knowledge of the preamble symbols of the IEEE 802.11 a/g standards, while it does not require the impulse response of the channel. Numerical results obtained through computer simulation show that the bit error rate (BER) performance for the proposed IQ imbalance estimation scheme has a degradation of about 4 dB with a large DC offset, frequency offset, and IQ imbalance.

Non-Orthogonal Access Scheme over Multiple Channels with Iterative Interference Cancellation and Fractional Sampling in MIMO-OFDM Receiver

Abstract: A diversity scheme with Fractional Sampling (FS) in OFDM receivers has been investigated recently. FS path diversity makes use of imaging components of a desired signal transmitted on an adjacent channel. In the previous literature, a non-orthogonal access scheme over multiple channels with iterative interference cancellation (IIC) and FS was proposed. The conventional scheme has shown that the imaging component is transmitted non-orthogonally and path diversity is realized with FS and IIC. However, the conventional scheme does not take into account a spatial multiplexing transmission scheme such as multiple-input multiple-output (MIMO). Therefore, this paper proposes a MIMO-FS scheme with IIC and evaluates its performance through computer simulation. It is shown that in the MIMO situation with channel coding the proposed system improves the performance by 1.5dB at the BER of 10-5 compared to a system without imaging components.

Sampling Rate Selection for Fractional Sampling in OFDM

Abstract: Through fractional sampling, it is possible to separate multi- path components and achieve diversity. However, power consumption grows as the sampling rate increases. In this paper, a novel sampling rate selection scheme in OFDM according to multipath environments is proposed. Numerical results through computer simulation show that the proposed sampling rate selection scheme reduces power consumption by decreasing the sampling rate when delay spread is small.

Cognitive Radio Techniques Under Practical Imperfections: A Survey

Abstract: Cognitive radio (CR) has been considered as a potential candidate for addressing the spectrum scarcity problem of future wireless networks. Since its conception, several researchers, academic institutions, industries, and regulatory and standardization bodies have put their significant efforts toward the realization of CR technology. However, as this technology adapts its transmission based on the surrounding radio environment, several practical issues may need to be considered. In practice, several imperfections, such as noise uncertainty, channel/interference uncertainty, transceiver hardware imperfections, signal uncertainty, and synchronization issues, may severely deteriorate the performance of a CR system. To this end, the investigation of realistic solutions toward combating various practical imperfections is very important for the successful implementation of cognitive technology. In this direction, first, this survey paper provides an overview of the enabling techniques for CR communications. Subsequently, it discusses the main imperfections that may occur in the most widely used CR paradigms and then reviews the existing approaches toward addressing these imperfections. Finally, it provides some interesting open research issues.

User pairing algorithm with SIC in non-orthogonal multiple access system

Abstract: As one of the candidate wireless access techniques of 5G system, non-orthogonal multiple access (NOMA) is a power domain non-orthogonal multiple-access technique, which can greatly enhance spectral efficiency and system capacity. This paper mainly focus on user pairing and access theme of NOMA system, and respectively presents channel state sorting pairing algorithm (CSS-PA) as user pairing (UP) theme and user difference selecting access (UDSA) algorithm as new user access theme. The two new algorithms are proposed out of considerations on the features of NOMA system with a successive interference cancellation (SIC) receiver, and take the users' channel conditions into account, which is pairing the users with the most distinctive channel conditions. Analytical and simulation results demonstrate that the new algorithms can improve system capacity greatly compared to the existing algorithms while guarantee the user fairness. Furthermore, we discuss to apply SIC with interference rejection combining (IRC) receiver into the NOMA/MIMO system, which is a possible extension of NOMA system combined with multi-antennas, and simulation result shows that the performance gain of IRC-SIC over MRC-SIC can achieve about 2dB in high signal-to-noise ratio situation.

Enhanced 5G Cognitive Radio Networks Based on Spectrum Sharing and Spectrum Aggregation

Abstract: In this paper, new enhanced cognitive radio networks (E-CRNs) based on spectrum sharing (SS) and spectrum aggregation (SA) are proposed for fifth generation (5G) wireless networks. The E-CRNs jointly exploit the licensed spectrum shared with the primary user (PU) networks and the unlicensed spectrum aggregated from the industrial, scientific, and medical bands. The PU networks include TV systems in TV white space and different incumbent systems in the long term evolution time division duplexing bands. The harmful interference from the E-CRNs to the PU networks are delicately controlled. Furthermore, the coexistence between the E-CRNs and other unlicensed systems, such as WiFi, is studied. The E-CRNs framework including dynamic spectrum management (DSM) is designed for the key parameters of licensed SS and unlicensed SA. The essential tradeoff between sharing efficiency and aggregation efficiency for the E-CRNs is discussed. Based on this tradeoff, a spectrum lean-management scheme is proposed to fulfill the DSM. Moreover, a water-filling algorithm is designed to dynamically access the available spectrum. Numerical results demonstrate that the proposed E-CRNs can significantly improve the system performance in terms of data rate, outage probability, and spectrum efficiency. In particular, the E-CRNs framework provides a spectrum usage prototype for 5G wireless communication networks.

Eigenvalue-Based Sensing and SNR Estimation for Cognitive Radio in Presence of Noise Correlation

Abstract: Herein, we present a detailed analysis of an eigenvalue-based sensing technique in the presence of correlated noise in the context of a cognitive radio (CR). We use standard-condition-number (SCN)-based decision statistics based on asymptotic random matrix theory (RMT) for the decision process. First, the effect of noise correlation on eigenvalue-based spectrum sensing (SS) is analytically studied under both the noise-only and signal-plus-noise hypotheses. Second, new bounds for the SCN are proposed to achieve improved sensing in correlated noise scenarios. Third, the performance of fractional-sampling (FS)-based SS is studied, and a method to determine the operating point for the FS rate in terms of sensing performance and complexity is suggested. Finally, a signal-to-noise ratio (SNR) estimation technique based on the maximum eigenvalue of the covariance matrix of the received signal is proposed. It is shown that the proposed SCN-based threshold improves sensing performance in correlated noise scenarios, and SNRs up to 0 dB can be reliably estimated with a normalized mean square error (MSE) of less than 1% in the presence of correlated noise without the knowledge of noise variance.

Maximum Torque Control of an Induction Machine in the Field Weakening Region

Abstract: In this paper,a new flux-weakening control method based on rotor flux orientation is presented to improve the current tracking capability and output characteristics of the motor torque,and the method is implemented in digital ac spindle driver system.Using Labview virtual oscilloscope to observe the real-time experimental data,the experimental results show that the method can effectively improve the dynamic response of motor as well as the output characteristics of the motor torque.