Yasutaka Ogawa

A MIMO-OFDM system for high-speed transmission

We propose new signal detection for space division multiplexing in a MIMO-OFDM system for high data rate transmission. Channel estimation is very important for suppressing the interference and demultiplexing the signals. In a wireless LAN system, such as IEEE 802.11a, only a few training symbols are inserted in each subcarrier. We propose a channel estimation method for the MIMO-OFDM system with two training symbols per subcarrier. The basic idea is to estimate the time-domain channel responses between the transmit and receive antennas. Applying the fast Fourier transform to them, the array response vectors for each subcarrier are calculated. Then, we can obtain the adaptive weights to cancel the interference. We show that employing training symbols having a lower condition number of a matrix used for the channel estimation improves the estimation accuracy.

Performance Evaluation of a Multi-User MIMO System With Prediction of Time-Varying Indoor Channels

In this paper, the performance of a multi-user multiple-input multiple-output (MIMO) system in time-varying channels is evaluated using measurement data. We consider the multi-user MIMO system using a block diagonalization (BD) scheme and an eigenbeam-space division multiplexing (E-SDM) technique. In an ideal case, the BD scheme eliminates inter-user interference, and the E-SDM technique suppresses inter-stream interference. In actual radio environments, however, channels change over time. This causes interference in the multi-user MIMO system even though the BD scheme and the E-SDM technique are used. To overcome this problem, the authors have developed a simple channel prediction scheme on the basis of a linear extrapolation and have demonstrated its effectiveness by computer simulations assuming the Jakes model. To verify the performance of the channel prediction scheme in actual environments, we conducted a measurement campaign in indoor environments and measured a large amount of channel data. Using these data, we examined the channel transition and channel tracking with the prediction method. Then we obtained the bit-error rate (BER) performance. The prediction technique was shown to track the channel and improve the BER performance almost to that in the ideal time invariant case.

Channel and frequency offset estimation for a MIMO-OFDM system

An OFDM technique has been utilized for wireless local area networks (WLANs). Spatial division multiplexing using a multiple-input multiple-output (MIMO) technique has been studied to increase the transmission rate to over 100 Mbps. Before we can detect the transmitted data, we need AGC adjustment, timing synchronization, frequency offset estimation, and channel estimation using a preamble. The current WLAN system with a single transmit antenna, based on the IEEE 802.11a standard, uses a four OFDM symbol duration preamble. However, the preamble period proposed so far for the MIMO-OFDM system grows linearly with the transmit antenna number. This results in an increased overhead, and the conventional technique is not efficient. In this paper, we present a channel and frequency offset estimation scheme using a preamble with four OFDM symbol duration for the MIMO-OFDM system in WLANs. This preamble has the same duration as that of the IEEE 802.11a standard, and does not increase the overhead. Computer simulation results are provided to demonstrate the performance of the proposed scheme.

Channel Estimation and Signal Detection for Space Division Multiplexing in a MIMO-OFDM System

We consider space division multiplexing in a MIMO-OFDM system for high data rate transmission. Channel estimation is very important for suppressing interference and demultiplexing signals. In a wireless LAN system such as IEEE 802.11a, only a few training symbols are inserted in each subcarrier. First, we propose a channel estimation method for a MIMO-OFDM system with two training symbols per subcarrier. The basic idea is to estimate the time-domain channel responses between the transmit and receive antennas. The array response vectors for each subcarrier are calculated by applying a fast Fourier transform to them. We then can obtain the adaptive weights to cancel the interference. We show that employing training symbols having a lower condition number of the matrix used for the channel estimation improves the estimation accuracy. Furthermore, we show the bit error rate for several signal detection schemes using the above estimated channel. It is shown that an ordered successive detection based on an MMSE criterion has excellent performance, that is, it can achieve higher-speed transmissions with a lower transmit power.

Reduction of the Amount of Channel State Information Feedback in MIMO-OFDM Eigenbeam-Space Division Multiplexing Systems

MIMO space division multiplexing in an OFDM system (MIMO-OFDM) can achive high-data-rate transmission without additional frequency spectra. Furthermore, eigenbeam-space division multiplexing (E-SDM) which is also called the singular value decomposition (SVD) algorithm can provide maximum throughput in the MIMO channel when channel state information (CSI) is available at the transmitter. When the uplink and downlink channels are not reciprocal as in a FDD system, we need to feed back the CSI from the receiver to the transmitter. However, capacity is limited because CSI feedback is needed for each subcarrier in an OFDM system. This paper proposes the feedback of the time-domain channel estimated using the minimum mean square error method. The proposed method can reduce the amount of feedback information, and reveals better bit error rate performance than the other schemes.

Considerations on a multi-user MIMO system using channel prediction based on an AR model

We consider a multi-user multiple-input multiple-output (MIMO) system using block diagonalization and eigenbeam-space division multiplexing to suppress inter-user interference and inter-stream interference. In time-varying environments, the performance seriously degrades due to mistracking of beamforming. A channel prediction scheme can eliminate the effect of the time-varying environments. In this paper, using indoor measurement data, we evaluate the bit error rate (BER) performance of a multi-user MIMO system with channel prediction based on an autoregressive model. It is shown that the proposed channel prediction technique can improve the BER performance significantly.

Multi-user MIMO system with channel prediction for time-varying environments

The performance of a downlink multi-user MIMO system seriously degrades in time-varying environments because MIMO channels change during the time interval between transmission parameter determination and actual MIMO transmission. Channel prediction techniques have been proposed to improve the performance in dynamic environments. In this paper, based on indoor measurement data, we show the effect of the linear channel extrapolation, and evaluate the bit error rate performance of the multi-user MIMO system with the channel prediction technique.

Accuracy evaluation of DOA estimation with multi-band signals

The method to estimate direction of arrival (DOA) with multi-band signals is proposed in this paper. The MUSIC method, which is one of the conventional super-resolution DOA estimation methods, is applied to sets of snapshots filtered from the multi-band signal. In the beginning, a set of snapshots is extracted by the narrow-band filter (NBF) for the lowest frequency where the half wavelength of center frequency equals the array antenna spacing for a uniform linear array, and processed by the MUSIC method in order to avoid grating lobes. Next, using another set of snapshots in higher frequency, more precise DOA estimation is done in a narrower range with finer step angle. Therefore, this method can realize more accurate DOA estimation than the conventional method using a single set of snapshots. By examining RMSE and success probability of DOA detection, this method is compared with a conventional method.

DOA estimation of signals with frequency characteristics and different powers using a compressed sensing technique

In recent years, much attention has been paid to direction of arrival (DOA) estimation using a compressed sensing technique. In our previous study, we have proposed a method to estimate DOAs of multi-band signals with frequency characteristics. However, we have assumed that all the arrival waves have the same amplitude. In this paper, we propose DOA estimation of signals with frequency characteristics and different powers among the arrived signals. Furthermore, we evaluate the method regardless of whether we know the frequency characteristics in advance.

BP-based detection of spatially multiplexed 16-QAM signals in a fully massive MIMO system

A massive multiple-input multiple-output (MIMO) system using a couple of hundred antenna elements has been arising as an important technology to keep the communication range in higher frequency bands. A further enhancement to increase the number of both transmit and receive antennas will be the next step. It requires the complexity proportional to at least the third power of the number of antenna elements to detect spatially-multiplexed signals in general. However, the belief propagation (BP)-based detector is implementable with lower complexity, i.e., the order of square of the number of elements, and achieves very good BER performance in a QPSK modulated massive MIMO system. In this paper, we apply the BP algorithm to a 16-QAM modulated massive MIMO system and propose a sequential reliability update to exploit a difference in error tolerance. The BER evaluation results have shown that the BP works well for a 16-QAM signal detection and that the sequential update is effective to the M-QAM modulated systems.