Stable and reliable wireless communications are absolutely essential in achieving safe, efficient, and comfortable autonomous driving systems, and require more channel resources. Cognitive radio (CR) alleviates the spectrum shortage by exploiting spectrum resources that are not used by primary users (PUs). Conventional CR-based vehicle-to-everything (V2X) communications still suffer from spectrum scarcity when the demands for wireless resources are excessive. Most previous analyses of this problem have adopted too simple models for V2X that assume constant vehicle velocity and that coarsely discretize vehicle positions. More realistic models for V2X are too topologically complex and too dynamically variant to find stable solutions of optimization problems by using conventional off-policy-based reinforcement learning (RL) algorithms such as Q-learning and deep Q-network (DQN) based on reply memories. Considering the above situation, this paper firstly builds a precise and realistic autonomous driving testbed by 3D engine. In the testbed, all vehicles move in an autopilot mode with random velocity and direction, which can provide more realistic traffic flow, positions, and motion for all vehicles. Due to the constrain of Kullback-Leibler divergence between updated and previous policies, on-policy RL algorithms such as proximal policy optimization (PPO) can find stable solutions to complex optimization problems. Inspired by this property, we expand the single-agent RL algorithm PPO into a multi-agent algorithm MA-PPO (multi-action proximal policy optimization). Computer simulations using the new testbed show the MA-PPO algorithm can gradually converge to more stable solutions and can achieve more steady and efficient data transmission than DQN.

As a new massive multiple-input multiple-output (MIMO) unsourced random access scheme for wireless channels, this paper proposes a slotted polar random spreading scheme. In the proposed scheme, the transmission frame is partitioned into several slots and each user independently selects one slot for message transmission. The above-mentioned message is divided into three parts: The first part indicates which slot is selected while the second one corresponds to pilot and spreading sequence mapping. The remaining part is polar encoded and spread over the selected slot. On the receiver side, a low-complexity activity detection (AD) is composed of the energy detector (ED) and covariance-based maximum likelihood detector (CB-MLD). Using the AD's output along with estimated channel frequency responses, the demodulator provides soft information on the coded bit sequences for single-user polar decoders that can extract the message bit sequences. For further improvement with low-complexity, successive interference cancellation (SIC) is employed as a multiuser detector. Computer simulations for 100-bit transmission per message demonstrate that the proposed scheme can outperform the conventional state-of-art scheme called FASURA, with a large number of active users, and requires lower complexity.

For 5G massive MIMO systems, hybrid beam-forming (HB) has been investigated thoroughly because it is composed of analog beamforming (AB) and digital beamforming (DB), and can reduce the number of baseband and RF circuits drastically. However, HB still has a major problem of pilot contamination and thus suffers from serious degradation of the channel estimation accuracy, when the same pilot signals are shared among multiple user terminals. To cope with this problem under time-varying channel conditions, we propose a method for adaptively predicting downlink (DL) channels while mitigating the pilot contamination. Considering time division duplex (TDD) multiuser MIMO communications, the proposed scheme firstly estimates an average angle of arrival (AoA) for each user’s cluster by applying multiple signal classification (MUSIC) to the received (Rx) pilot signals, which can reconstruct the channel frequency responses of the interfering users and then extracts the desired channel frequency responses from the combined ones. Since the desired channel frequency responses can be considerably extracted, the proposed scheme coarsely compensates for time-variation of the Rx signal by predicting the Doppler effect of each cluster. The residual time-variation can be tracked and removed using detected signals of all the streams in a decision-directed manner. Finally, the estimated total time-variation is used to predict the DL channel frequency response. Computer simulations demonstrate that the proposed scheme can accurately track the time-varying channels while mitigating the pilot contamination.

Polar codes, which can be classified into GN-coset codes as well as Reed-Muller (RM) codes, has been applied to wireless communications. Considering that generator matrices of polar and RM codes can be obtained by selecting some row vectors from GN, this paper proposes a row-selection criterion for constructing GN-coset codes that can maintain good transmission performance of orthogonal frequency-division multiplexing (OFDM) over frequency selective fading channels while alleviating the performance degradation of RM codes with high code rate. Since the proposed criterion exploits channel state information (CSI) of the frequency selective channels, information on the selected or deleted row vectors should be fed back to the encoder. In addition, a new feedback system that aims to reduce an amount of feedback information is proposed. Computer simulations demonstrate that the proposed code construction scheme is superior to the conventional polar and RM codes in terms of block error rate (BLER) performance with a wide range of the code rate, when belief propagation (BP) based decoding is employed. Especially, the proposed scheme can achieve average Eb/N0gain of 3-7 dB over the polar codes of the 5G standard. In addition, the proposed feedback system with a wide range of the code rate can reduce more than 50% of feedback information in comparison with the conventional one.

The space-based automatic identification system (AIS) has attracted much attention because the system can receive AIS signals from ships on the high seas. As its serious problem, multiple AIS packets can collide at one satellite because it has a wide coverage area. Parallel interference cancellation (PIC) based on Viterbi algorithm (VA) is very effective in separating the collided packets and shows an excellent bit error rate (BER) performance under the condition that Doppler frequencies, channel impulse responses, and propagation delay time are ideally estimated. When the estimation of those channel parameters is not sufficiently accurate with desired to undesired signal power ratio (DUR) being low, however, the BER of PIC can be seriously degraded. In this paper, we propose a novel iterative channel estimation scheme for each channel parameter to improve the estimation accuracy even under the low DUR condition. The least squares and quasi-Newton methods are applied to the estimation of the channel impulse responses and Doppler frequencies, respectively, besides coarse estimation using correlators. The correlation-based estimation of the propagation delay time is repeated. Computer simulations demonstrate that the proposed scheme can estimate the channel parameters more accurately, which leads to remarkable improvement in the BER performance.

The polar code has attracted much attention because it has been adopted as the coding scheme for control channels of the fifth-generation mobile communications (5G) and beyond. In the encoding process, some information bits that are likely to be incorrectly decoded are selected as the frozen bits and fixed to a certain value. Almost all conventional schemes carry out this selection on the assumption of the additive white Gaussian noise (AWGN) channel. To improve the decoding performance, a conventional belief propagation (BP) decoder bit-flips some decoded bits belonging to the critical set (CS). CS is a set of indices of which information bits are not the frozen bits but tend to be incorrectly decoded. However, the combination of these conventional encoding and decoding schemes may incur degradation of block error rate (BLER) over frequency selective fading channels, because channel state information (CSI) is not considered at all. To alleviate the BLER degradation, this paper proposes a joint encoding and decoding scheme of the polar code that take into account CSI on orthogonal frequency-division multiplexing (OFDM) transmission. Firstly, the BP decoder of the proposed scheme calculates likelihood ratios (LRs) of the information bits from LRs of the received sequence, on the basis of the CSI during the estimation period. Secondly, some information bits are assigned to the frozen bits on the criterion of the absolute values of their log LRs (LLRs). Information on the frozen bits is fed back to the encoder. Thirdly, some information bits excluding the frozen bits are assigned to CS on the same criterion during the decoding period. Finally, the bits belonging to CS are bit-flipped in ascending order of reliability. Computer simulations of OFDM transmission over a multipath channel demonstrate that the proposed assignment of the frozen bits can gain average Eb/N0of 3 dB over the conventional one at the same average BLER, and that the proposed assignment of CS outperforms the conventional one while reducing an amount of computational complexity by 75%.

Initially, the automatic identification system (AIS) aims at ship-to-ship or ship-to-coast wireless communications. To enhance AIS, Japan Aerospace Exploration Agency (JAXA) has conducted an experiment named space based AIS experiment (SPAISE), which enables satellites to observe AIS signals that are transmitted from ships across the open ocean and affected by Doppler shift. This experiment has shown that conventional and simple detection schemes for the satellites cannot always operate well, because the wide coverage of the satellites causes frequent collisions of several AIS signal packets. To cope with such a problem, a multiuser detection scheme such as parallel interference cancellation (PIC) has been used for the signal detection. However, the bit error rate (BER) performance is degraded when channel parameters such as Doppler frequencies are estimated by the correlation between the received signals and the known training sequence. To alleviate the degradation, this paper proposes to employ a highly accurate estimation scheme based on the quasi-Newton method for Doppler frequencies that affect the BER performance most seriously. Computer simulations under Rician fading channel conditions demonstrate that PIC employing the proposed method can improve the BER performance drastically.

A quasi-constant-amplitude scheme for orthogonal frequency-division multiplexing (OFDM) over wireless channels is proposed. To reduce the high peak-to-average power ratio (PAPR) of OFDM, a conventional scheme called constant envelope OFDM (CE-OFDM) transforms the OFDM signal into a phase modulated signal. Although CE-OFDM considerably increases an amount of computational complexity, the proposed scheme does not require such an amount of complexity and can suppress levels of out-of-band emission (OOBE) than CE-OFDM. The transmitter of the proposed scheme decomposes an OFDM signal into two constant-amplitude signals so as to reduce PAPR to the lowest level of 0 dB. Since the two signals cause high levels of OOBE, these signals are passed into a low-pass filter (LPF). The two LPF outputs, of which amplitudes are quasi-constant, are transmitted from the same transmit antenna at different timing. On the receiver side, two received signals that originate from the two LPF outputs and that propagate through a wireless channel are combined to regenerate the original OFDM signal. Computer simulation results demonstrate that the proposed scheme with a properly designed LPF is much superior to CE-OFDM in bit error rate (BER) performance while reducing OOBE to much lower levels. It is also shown that although LPF increases PAPR of the proposed scheme from 0 dB to about 2.5 dB, the PAPR is 8 dB lower than the conventional OFDM signal at the complementary cumulative distribution function of 0.001, which can verify the effectiveness of the proposed scheme.

A constant-amplitude modulation scheme for orthogonal frequency-division multiplexing (OFDM) over wireless channels is proposed in this paper. To alleviate the high peak-to-average power ratio (PAPR) of OFDM signals, the proposed scheme decomposes an OFDM signal into two constant-amplitude signals, which are transmitted at different timing. On the receiver side, the original OFDM signal is regenerated by combining two received signals that originate from these two constant-amplitude signals, which are propagated through the wireless channels. As a conventional constant-amplitude OFDM scheme, the constant envelope OFDM (CE-OFDM) scheme transforms the OFDM signal into a phase modulated signal. Computer simulations make a comparison between the proposed and conventional schemes, and demonstrate that the proposed scheme is much superior to CE-OFDM in bit error rate (BER) performance while both the schemes have almost the same out-of-band spectral characteristics.

Non-orthogonal multiple access (NOMA) is one of the most promising techniques to achieve high spectral efficiency for 5G. In the NOMA downlink, a transmitter allocates different power levels to users and linearly combines user signals using the square roots of the power levels. A constellation point of the combined signal can be very close to other points, which degrades bit error rate (BER) performance severely. To overcome such degradation, the proposed NOMA system rotates phases of the user signals and then linearly combines the resultant signals. On the receiver side, multiuser detection (MUD) is introduced so as to improve BER performance more than successive interference cancellation (SIC), which the conventional scheme employs. Since the proposed scheme with phase rotation (PR) for 2-user signal transmission has been thoroughly investigated, this paper considers 3-user transmission in the proposed NOMA scheme and proposes one method to optimize two angles of PR, whereas another method previously proposed by the authors can control only one angle. Computer simulations under the 3-user condition demonstrate that the proposed scheme employing PR and joint MUD and SIC for signal detection is much superior to other schemes in downlink BER performance and that the two optimization methods bring about almost the same BER.

Massive multiple-input multiple-output (MIMO) will be employed in the 5th generation mobile communications (5G). To implement the massive MIMO, hybrid beamforming (HB) is one of the most promising techniques, because HB is composed of the analog beamforming (AB) and the digital beamforming (DB) and thus can decrease the number of baseband and radio frequency (RF) circuits significantly. Furthermore, HB can reduce a much larger amount of cost and power consumption than the full DB (FDB) configuration, which requires one baseband and RF circuit for each antenna element. This paper proposes a scheme to estimate both phases for phase rotators in AB and a precoding matrix for DB so that HB can approximate the block diagonalization (BD), which can nullify interference from the undesired users and form efficient transmit beams. For time division duplex (TDD) multiuser MIMO communications, the proposed scheme estimates the FDB channel matrix in the uplink (UL) and the phase for the phase rotators of AB in the downlink (DL). After obtaining an equivalent channel matrix from both the estimated FDB channel matrix and the AB precoding matrix, the scheme estimates the DB precoding matrix in DL from the equivalent channel matrix so that HB can approximate BD in DL. Computer simulations demonstrate that HB employing the proposed scheme can achieve DL average bit error rate (BER) performances that are little inferior to those of FDB.

As a multiple access technique candidate of 5G, non-orthogonal multiple access (NOMA) has attracted much attention for its high spectral efficiency. On its receiver side, successive interference cancellation (SIC) cancels the dominant interference and detects the desired signal. When a transmit power level allocated to one user is roughly equal to those allocated to other users, however, the bit error rate (BER) performance degrades severely. To alleviate such a problem, this paper proposes a novel NOMA scheme with phase rotation, and analyzes the optimum angle of the phase rotation in the case of two modulation schemes. Even when multiuser detection (MUD) that simultaneously detects both desired and interfering signals is employed, the BER performance still degrades due to low minimum distance between the superposed constellation points. To improve the BER performance, this paper also proposes a joint MUD and SIC scheme that exploits the advantages of both MUD and SIC. Computer simulations demonstrate that the joint MUD and SIC scheme with the phase rotation outperforms other detection schemes with or without the phase rotation.

To cope with the interference problem in three-cell wireless relay systems, this paper proposes two schemes that perform interference suppression and multiuser detection. The proposed schemes do not require channel state information (CSI) feedback, and their computational complexity is much less than that of the maximum likelihood detection (MLD), which is considered in the optimal detection scheme. Of the two proposed schemes, the minimum mean-square error (MMSE)-based scheme estimates the weight coefficients for the interference suppression under the MMSE criterion. The other proposed scheme, the recursive least squares (RLS)-based scheme, directly estimates the weight coefficients using the RLS algorithm. The RLS-based scheme only requires two preamble sequences, whereas both the MMSE-based schemes and the MLD require the knowledge of all the three preamble sequences. Therefore, the RLS-based scheme can be considered more feasible. Moreover, computer simulations results and theoretical average bit error rate (BER) upper bounds of orthogonal frequency-division multiplexing transmission under three-cell and frequency-selective fading conditions were provided. It was observed that simulation results are consistent with theoretical upper bounds and that the RLS-based scheme achieves a BER performance that is identical to that of the MMSE-based scheme with perfect CSI while requiring much less computational complexity than the MLD.

To cope with interference in three-cell multiple relay systems, this paper proposes schemes that detect two users' signals while linearly suppressing one remaining user's signal. The proposed schemes do not require channel state information (CSI) feedback and can drastically reduce the computational complexity compared to the maximum likelihood detection (MLD), which is the optimal signal detection and detects all three users' signals. As one proposed scheme, a minimum mean-squared error (MMSE) scheme estimates weight coefficients for the interference suppression under the MMSE criterion, and thus needs to estimate CSI of all the users by using all the three preamble sequences like MLD. Another proposed scheme called a recursive least squares (RLS) scheme directly estimates the weight coefficients by the RLS algorithm. In contrast with the MMSE scheme and MLD, the RLS scheme needs to know only two preamble sequences and thus is more feasible. Computer simulations of orthogonal frequency-division multiplexing (OFDM) transmission under three-cell and frequency selective fading conditions show that the proposed schemes can maintain good bit error rate in contrast with a conventional scheme for two-cell systems, and that the RLS scheme can outperform the MMSE scheme with estimated CSI when decision-directed estimation with error selection is applied.

In order to cope with severe interference in heterogeneous networks, this paper proposes a semi-blind interference cancellation scheme, which does not require multiple receive antennas or knowledge about training sequences of the interfering signals. The proposed scheme performs a suboptimal joint channel estimation and signal detection (JCESD) based on a quantized channel approach in order to semi-blindly estimate the channel, while reducing the computational complexity of the optimum JCESD drastically. In addition, a recalculation scheme is introduced to avoid inaccurate channel estimates due to local minima. Using the channel estimated by the proposed JCESD, the proposed scheme performs multiuser detection (MUD) of both the desired and interfering signals during the data period. Computer simulations under one and two interfering signals conditions show that the proposed scheme outperforms a conventional one based on the generalized Viterbi algorithm, and can achieve almost the same bit error rate performance as the MUD with channels estimated with additional training sequences of the interfering signals, while reducing the computational complexity significantly compared with the full search for all transmitted signal candidates.

In two-cell scenarios with half-duplex relays, the number of diversity branches provided by the relays is sufficient to suppress one interfering signal. However, the same diversity branches are not enough to suppress two interfering signals in three-cell systems. To cope with such a problem, this paper proposes joint interference suppression and multiuser detection for the three-cell wireless relay systems. The proposed scheme estimates weight coefficients for the interference suppression under the minimum mean-square error (MMSE) criterion, while requiring a less amount of computational complexity than the maximum likelihood detection (MLD). In addition, the proposed scheme does not require channel state information (CSI) to be fed back, but needs to know all three preamble sequences. Computer simulations of orthogonal frequency-division multiplexing (OFDM) transmission under three-cell and frequency selective fading conditions are conducted. It is shown that the proposed scheme can maintain good bit error rate (BER) performance in contrast with the conventional scheme for the two-cell system and is inferior to MLD, which is the optimal signal detection but requires much more complexity than the proposed scheme.

In this paper, an adaptive codebook precoding scheme is proposed for time-varying multiple-input multiple-output (MIMO) channels with feedback delay. The proposed scheme updates its codebook on the basis of the spherical cap codebook (SCC) approach. In contrast with the conventional radius calculation for SCC, the proposed scheme does not need additional feedback of the cap radius or offline radius calculation, but only adapts the radius according to a previously selected codeword. In addition, the Kalman filter using the differential model as its process equation is employed to predict MIMO channels and to select a suitable codeword from the codebook. Since the Kalman filter does not require information on the maximum Doppler frequency, the proposed scheme, which is a combination of the self-adaptive SCC and the Kalman filter, can work well even when the maximum Doppler frequency is not exactly known. Computer simulations under 4-by-4 MIMO channels with 2 data streams and a 6-bit codebook demonstrate that the proposed scheme can improve the system capacity in the same way as the conventional scheme does, which needs exact information on the maximum Doppler frequency in contrast to the proposed scheme. When the different channel model is used, it is shown that the proposed self-adaptive SCC can still provide considerable capacity gain, while the conventional scheme can not do so.

Applications of millimeter-wave (mm-wave) to high mobility wireless communication scenarios such as high speed trains (HSTs) have been discussed. In the HST scenarios, not only phase noise but also Doppler shift should be considered. In previous works, our proposed iterative phase noise compensation method was evaluated with a dynamic channel model with high Doppler shift. The efficacy of the iterative method, employing symbol level decision directed channel estimation (SDDCE), was demonstrated with the dynamic channel model. However, parameters of the channel model need to be obtained further for the HST environments. In this paper, we construct a linear HST environment, and analyse the propagation characteristics of the HST scenario with a ray tracing method at 60 GHz band. With the simulation, we obtain the received power, the K factor of the Rician model, delay spread, and angular spread characteristics of the HST environment. It is shown that the K factor is large when the distance between the transmit (Tx) and receive (Rx) antennas is short, and that when the distance between the Tx and Rx is large, the level of fading becomes large, which is much different from the indoor environment. We also complete the dynamic channel model with the obtained statistical parameters, which can simulate the dynamic channel fluctuation due to the Doppler shift.

OFDM transmission schemes are adopted in the integrated services digital broadcasting-terrestrial (ISDB-T), the downlink of long term evolution (LTE), etc. In most cases, there are not many delayed paths in the propagation environments, i.e., the wireless channels are likely to be sparse. In addition, when the receiver moves rapidly, the accuracy of channel estimation deteriorates significantly. In order to alleviate the deterioration, the iterative channel estimation scheme with the tap selection and the least mean squares (LMS) algorithm has been studied. For further improvement of the channel estimation accuracy, this paper investigates a channel estimation scheme employing the optimization method with L1-norm regularization, called fast iterative shrinkage-thresholding algorithm (FISTA), and proposes an iterative receiver employing such a channel estimation scheme for OFDM systems. For evaluating the performance of the proposed scheme, computer simulations are conducted under the condition of ISDB-T with the scattered pilots (SP)-OFDM signal. It is shown that the proposed method has much better accuracy in the estimation of the sparse channel impulse response than the conventional method.

Recent demand for capacity increase in mobile communications urges the development of both multiple- input multiple-output (MIMO) and small cells. However, overlapping coverage areas between neighboring small cells results in interference-limited networks, where the capacity of the network is severely degraded without superior intercell interference management (IIM) techniques. As one of the superior IIM techniques, the power control intercell interference coordination (ICIC) optimizes downlink transmit powers in the network. This paper proposes an IIM scheme consisting of both neural networks (NNs) power control on the transmitter side and interference cancellation (IC) on the receiver side. Computer simulations examine networks of MIMO systems with the power optimization using some ICIC algorithms: NN, the greedy search, the belief propagation (BP), and the maximum power, combined with IC on the receiver side. In addition, the deep learning, a breakthrough technique for NN with multi-layer structures, is also applied to mobile communications. The results show that the performance of NN is very close to that of the greedy search and superior to that of BP. Complexity of NN is much less than that of BP, and thus NN is suitable for IIM. It is also demonstrated that employing IC provides high capacity gain.

As a signal detection method for multiple-input multiple-output (MIMO) communications, this paper proposes multi-stream constrained search (MSCS) that achieves very good trade-off between computational complexity and bit error rate (BER) performance. The proposed method sets a minimum mean-squared error (MMSE) detection result to the starting point. From this point, MSCS searches for signal candidates in multi-dimensions of the noise enhancement from which the MMSE detection suffers. In the search, some streams of the signal candidates are fixed at constellation points. Among the obtained signal candidates, the detected signal is selected as the one that minimizes the log likelihood function. Furthermore, this paper proposes stream selection-MSCS (S-MSCS) that selects the constrained streams under the criterion of small equivalent amplitudes of channels caused by the MMSE detection. Setting the number of patterns of constrained streams to just one can reduce complexity, and selecting the constrained streams on the basis of the equivalent amplitude can maintain excellent BER performance. Computer simulations under 8 × 8 MIMO channel conditions with 16QAM demonstrate that S-MSCS can maintain only 0.5 dB degradation of the average BER performance from the maximum likelihood detection (MLD), while reducing the computational complexity to about one third of that of QR decomposition with M algorithm (QRM)-MLD.

The performance of 30 Gbps super high bit rate mobile communications is evaluated by computer simulation using channel data collected in 11 GHz band 24×24 MIMO outdoor propagation experiments, and the feasibility of 11 GHz band 30 Gbps transmission is verified. To achieve the super high bit rate mobile communications, 10 Gbps transmission using 11 GHz band 8×16 MIMO has been verified in outdoor transmission experiments. In addition, channel measurement and analysis have been conducted in 11 GHz band 24×24 MIMO radio propagation experiments. Although 24×24 MIMO transmission is expected to achieve a bit rate exceeding 30 Gbps, transmission experiments have not yet been performed due to the hardware limitations. In this paper, computer simulations based on 24×24 MIMO-OFDM eigenmode transmission are conducted by utilizing channel data measured using an 11 GHz band 24×24 MIMO channel sounder. This paper shows that throughput exceeding 30 Gbps is achieved in 11 GHz band mobile environments, and clarifies the requirements for the average signal-to-noise ratio, channel conditions, and accuracy of channel state information to achieve 30 Gbps throughput over a real 11 GHz band 24×24 MIMO channel.

This paper proposes interference suppression schemes by linear combining for wireless multiuser relay communications. Interference from base stations and relays in neighboring cells degrades bit error rate (BER) performance of mobile stations (MSs) near cell boundaries. To suppress such interference for half-duplex relay systems, the proposed methods linearly combine received signals of the first and second phases at MS. Without channel state information (CSI) feedback, weight coefficients for the linear combining are first evaluated under the minimum mean-squared error (MMSE) criterion and then estimated by the recursive least-squares (RLS) algorithm. The MMSE combining requires information on preamble symbols of all MSs for channel estimation whereas the RLS-based linear combining requires only information on those of the target MS. In addition to the preamble symbols, the RLS algorithm can use detected symbols, which performs the decision-directed estimation. Computer simulations for orthogonal frequency-division multiplexing (OFDM) transmission under two-cell and frequency selective fading conditions are conducted. It is demonstrated that the RLS-based linear combining with the decision-directed estimation is superior to the RLS-based linear combining using only the preamble and can slightly outperform the MMSE combining with imperfect CSI under low average Eb/N0when the number of preamble symbols is as small as four.

This paper proposes an approximate block diagonalization (BD) method that does not require feedback of channel state information (CSI) by using the second-order statistics of channels for multiuser MIMO mobile communications. On the assumption that an incidence angle (angle-of-arrival) distribution in the uplink channel is the same as an angle-of-departure distribution in the downlink channel, the proposed scheme estimates the autocorrelation matrix of the downlink channel from the average and variance of incidence angles in the uplink. Since the proposed scheme uses the estimate of the autocorrelation matrix of the downlink channel, it performs eigenvalue decomposition of the estimated autocorrelation matrix whereas the conventional BD precoding performs singular value decomposition of the channel matrix. To verify the effectiveness of the proposed scheme, computer simulations are conducted. It is shown that the proposed scheme, which does not need CSI feedback, is little inferior in the channel capacity to the conventional BD precoding that requires CSI feedback.

This paper presents detailed results of 11 GHz band outdoor transmission experiments employing 8 × 16 MIMO-OFDM for 10 Gbps super high bit rate mobile communications. Super high bit rate mobile communications have been studied for future mobile communications, and to verify the feasibility, outdoor transmission experiments were performed. A mobile station (MS) with 8 transmitter antennas traveled along a measurement course while a base station (BS) with 16 receiver antennas stored the received signals, and then the throughput performance levels were evaluated by demodulating them in an off-line mode. This paper introduces specifications and a hardware configuration for the 11 GHz band 8×16 MIMO-OFDM experimental system with a signal bandwidth of 400 MHz. In addition, it presents the SNR distribution and delay spread that are calculated from the received signals in the measurement course used in the outdoor experiments. The experimental results show that for 11.8 Gbps transmission with 8 streams, 64QAM, and the coding rate of 3/4, throughput of greater than 10 Gbps is achieved in an 11 GHz band outdoor mobile environment.

Joint signal detection and channel estimation based on the expectation-maximization (EM) algorithm has been investigated for orthogonal frequency-division multiplexing (OFDM) mobile communications over fast- fading channels. In order to make the signal detection suitable for the iterative EM-based receiver with multiple antennas, this paper proposes spatial removal from the perspective of a message- passing algorithm on factor graphs. The spatial removal performs the channel estimation of a targeted antenna by using detected signals that are obtained from the received signals of all antennas other than the targeted antenna. It can avoid the repetitive use of unreliable received signals for consecutive signal detection and channel estimation. Computer simulations under fast-fading conditions demonstrate that appropriate application of the spatial removal can exploit such a removal effect and the spatial diversity, resulting in improvement of the packet error rate (PER).

ABSTRACT We develop an efficient hard detector for multiple‐input multiple‐output (MIMO) channels, which adaptively combines maximum‐likelihood detection (MLD) and minimum‐mean‐square error with a successive interference canceler together. Unlike the conventional joint combination scheme, which may suffer from considerable degradation in bit‐error‐rate (BER) performance over correlated channels and where only one data stream is detected by MLD, our proposed scheme adaptively controls the number of data streams to be detected by MLD based on an analytical characterization of reliability for the detection. Simulation results illustrate that near‐optimal BER performance can be obtained at much lower computational complexity by the proposed method as compared with existing techniques, regardless of the spatial correlation of the MIMO channels. Copyright © 2012 John Wiley & Sons, Ltd.

To maintain good transmission performance of orthogonal frequency-division multiplexing (OFDM) mobile communications over fast-fading channels, iterative maximum a posteriori (MAP) receivers that iterate channel estimation and signal detection on the basis of the expectation-maximization (EM) algorithm have been investigated. In order to make such a MAP receiver more robust against time-variant channels, this paper derives channel estimation with subcarrier removal from the perspective of a message-passing algorithm on factor graphs. The subcarrier removal estimates the channel frequency response by using the detected signals of all subcarriers other than that of a targeted subcarrier. This modification can avoid the repetitive use of incorrectly detected signals for the channel estimation. Computer simulations under fast-fading conditions demonstrate that the EM-based MAP receiver performing the subcarrier removal can improve the packet error rate (PER) drastically.

Super high bit-rate mobile communications have been investigated to achieve more than 10 Gbps bit-rate. This paper studies an experimental system that can achieve 5 Gbps throughput by using 11 GHz band radio frequency (RF) circuits and 4×4 MIMO-OFDM with 400 MHz wide bandwidth, of which feasibility is verified. The experimental system consists of (i) 11 GHz band RF circuits, (ii) FPGA boards with 800 MHz sampling DAC or ADC, and (iii) CPU boards that perform MIMO-OFDM transmission and reception processing in offline mode. The RF circuits employ a direct conversion method. Since IQ imbalance and phase noise in the RF circuits degrade transmission performance, this paper compensates for them by digital signal processing. The experimental system evaluates the transmission performance in 5 Gbps 4×4 MIMO-OFDM employing turbo detection, and it is shown that performance degradation of the experimental system to the simulation results can be limited to less than 1 dB by the compensation method for imperfection of the RF circuits. In addition, it is clarified that the turbo detection with two iterations can improve 6.0 dB at SNR to achieve 5 Gbps throughput.

This paper proposes a low-complexity signal detection algorithm for spatially correlated multiple-input multiple-output (MIMO) channels. The proposed algorithm sets a minimum mean-square error (MMSE) detection result to a starting point, and searches for signal candidates in multi-dimensions of the noise enhancement from which the MMSE detection suffers. The multi-dimensional search is needed because the number of dominant directions of the noise enhancement is likely to be more than one over the correlated MIMO channels. To reduce computational complexity of the multi-dimensional search, the proposed algorithm limits the number of signal candidates to O(NT) where NTis the number of transmit antennas. Specifically, the signal candidates, which are unquantized, are obtained as the solution of a minimization problem under a constraint that a stream of the candidates should be equal to a constellation point. Finally, the detected signal is selected from hard decisions of both the MMSE detection result and unquantized signal candidates on the basis of the log likelihood function. For reducing the complexity of this process, the proposed algorithm decreases the number of calculations of the log likelihood functions for the quantized signal candidates. Computer simulations under a correlated MIMO channel condition demonstrate that the proposed scheme provides an excellent trade-off between BER performance and complexity, and that it is superior to conventional one-dimensional search algorithms in BER performance while requiring less complexity than that of the conventional algorithms.

This paper proposes a new coherent detector that exploits the real zero (RZ) concept for signal recovery. The detector recovers the complex envelope consisting of in-phase (I) and quadrature (Q) components of linear quadrature amplitude modulation (QAM). The received signal before amplification is processed by RZ conversion, after which the converted signal can be amplified by a severely distorted amplifier. The RZ conversion combines the modulated received signal with a sinusoidal wave whose frequency is slightly outside the modulated frequency band, and the resultant signal is amplified to a saturated level. Next, the IQ detection applies the RZ concept to the IQ signal recovery. It utilizes a time to digital converter (TDC) for RZ timing estimation. A linear interpolation type TDC is introduced. Computer simulations demonstrate the effectiveness of the proposed detector. It is shown that error vector magnitude (EVM) of the recovered complex envelope is around -30 to -40 dB for a narrowband signal.

This paper proposes a precoding scheme for downlink multiuser MIMO-OFDM systems. The proposed precoding employs the minimum bit error rate (BER) criterion and estimates precoding matrices to minimize total BER of mobile stations by the steepest descent algorithm. As the cost function of the proposed scheme, an upper bound of the total BER is derived from the pairwise error probability (PEP) and is averaged with respect to channel state information (CSI) errors. Thus, the proposed scheme can be robust to imperfect CSI. Computer simulations under a frequency-selective fading condition demonstrate that the proposed precoder is more robust to the CSI errors than the zero-forcing (ZF) precoder, and that it is superior in BER to the conventional scheme.

This paper proposes an iterative receiver employing multiuser detection (MUD) and channel estimation for uplink MIMO-OFDM interleave-division multiple access (IDMA). IDMA can perform low-complexity MUD by employing a low-rate channel code and an individual interleaver for each user, and is expected to improve spectrum efficiency in mobile communications. However, an excellent channel estimator has not been proposed in the uplink MIMO-OFDM IDMA. This paper proposes the iterative receiver that repeats a joint processing of MUD and channel estimation by exploiting log-likelihood ratios of coded bits (bit LLRs) which channel decoders of all users provide. The receiver employs soft decision-directed channel estimation (SDCE) using the bit LLRs during data symbols, in addition to initial channel estimation (ICE) using known preambles. To improve an accuracy of the channel estimation, it performs tap selection (TS) that extracts only dominant paths from a channel impulse response estimated by ICE or SDCE. Moreover, this paper evaluates transmission performances of the proposed receiver, and shows that the receiver can achieve an excellent performance in 4-by-4 MIMO-OFDM IDMA with four users.

This paper proposes a peak-to-average power ratio (PAPR) reduction method that maintains an effect of linear precoding by block diagonalization (BD) for multiuser (MU) MIMO-OFDM systems. In the downlink MU-MIMO-OFDM, BD orthogonalizes multiple signals of all users by the linear precoding using channel state information, but the transmitted signal still has high PAPR due to OFDM characteristics. Therefore, BD suffers from waveform distortion caused by a nonlinear transmit power amplifier, especially when the number of transmit antennas is set large enough for the orthogonalization. This paper proposes BD transmission selected mapping (BD-SLM) that can reduce PAPR while maintaining the BD effect. BD-SLM performs the phase shift to modulation signals of all users before the linear precoding. From several phase sequences, it selects a phase sequence that minimizes the peak of the time-domain signals at all transmit antennas. Computer simulations demonstrate that BD-SLM can drastically reduce PAPR in 16 × 4 MIMO-OFDM with four users, and that it can alleviate the performance degradation even when the power amplifier causes nonlinear distortion.

This paper proposes a low-complexity algorithm to calculate log likelihood ratios (LLRs) of coded bits, which is necessary for channel decoding in coded MIMO-OFDM mobile communications. An approximate LLR needs to find a pair of transmitted signal candidates that can maximize the log likelihood function under a constraint that a coded bit be equal to either one or zero. The proposed algorithm can find such a pair simultaneously, whereas conventional ones find them individually. Specifically, the proposed method searches for such candidates in directions of the noise enhancement with the MMSE detection as a starting point. First, an inverse matrix which the MMSE weight matrix includes is obtained and then the power method derives eigenvectors of the inverse matrix as the directions of the noise enhancement. With some eigenvectors, one-dimensional search and hard decision are performed. From the resultant signals, the transmitted signal candidates to be required are selected on the basis of the log likelihood function. Computer simulations with 4×4 MIMO-OFDM, 16QAM, and a half-rate convolutional code demonstrate that the proposed algorithm requires only 1.0 dB more Eb/N0than that of the maximum likelihood detection (MLD) in order to achieve packet error rate of 10-3, while reducing the complexity to about 0.2% of that of MLD.

This paper proposes methods that can reduce peak- to-average power ratio (PAPR) while maintaining performance improvement by linear precoding for the eigenmode MIMO- OFDM transmission. In the eigenmode MIMO-OFDM system, a transmitter performs linear precoding using channel state information (CSI), and thus excellent transmission performance can be achieved. However, the transmitted signal still has high PAPR because of OFDM characteristics. To reduce such PAPR, this paper enhances selected mapping (SLM) and partial transmit sequence (PTS) which are known as PAPR reduction methods for OFDM. The enhanced methods, which are referred to as eigenmode transmission SLM (EM-SLM) and eigenmode transmission PTS (EM-PTS), can be applied to the eigenmode MIMO- OFDM without any performance degradation. Computer simulations demonstrate that in 4times4 MIMO-OFDM, the proposed methods can drastically reduce PAPR, and thus they can alleviate performance degradation due to nonlinear amplification.

This paper proposes an iterative OFDM millimeterwave receiver employing low-complexity decision-directed phase noise compensation (DD-PNC) to alleviate degradation due to the phase noise. High bit-rate OFDM transceivers based on the single-chip Si RF-CMOS IC technology in the 60-GHz millimeter-wave band have been extensively studied for wireless personal area network (WPAN) systems, and the relatively large phase noise in the phase locked loop (PLL) synthesizer severely degrades transmission performance. The proposed OFDM receiver iterates DD-PNC and decision-directed channel estimation (DDCE) by exploiting the output of the channel decoder. DDPNC estimates the phase noise each sampling time by using the decoder output, and then it removes the estimate from a time-domain received signal. In addition, DDCE estimates a channel impulse response by using the compensated received signal. Computer simulations demonstrate that in the 64QAM modulation with the coding rate of 3/4, the proposed receiver with DD-PNC and DDCE can perfectly remove the phase noise of -85 dBc/Hz at 1 MHz offset, and that it can alleviate the degradation of the channel estimation due to the phase noise.

This paper applies iterative multiuser detection employing new channel estimation to multicarrier interleave- division multiple access (MC-IDMA), known as OFDM-IDMA, which is expected to improve spectral efficiency in mobile communications. The MC-IDMA transmitter uses both a low-rate channel code and an individual chip interleaver for each user. The MC-IDMA receiver, which this paper investigates, repeats the iterative multiuser detection and soft decision-directed channel estimation (SDCE) by exploiting log-likelihood ratios (LLRs) of the coded bits which the MAP-based channel decoders for all users provide. SDCE estimates channel impulse responses of all users by the LMS algorithm, which aims to minimize the mean squared error between the received signal and its replica. This paper investigates the performance of MC-IDMA employing SDCE and compares it with those of three MC-CDMA techniques. Computer simulations demonstrate that MC-IDMA employing SDCE outperforms time-spread MC-CDMA and frequency-spread MC-CDMA, and that it can achieve almost the same bit error rate performance as chip-interleaved MC-CDMA while requiring lower complexity.

This paper proposes a minimum BER (MBER) based precoder that is robust to imperfect channel state information (CSI) for MIMO-OFDM mobile communications. The proposed MBER precoding aims to minimize BER of the maximum likelihood detection (MLD), on the condition that the transmitter can obtain only imperfect CSI owing to channel estimation and quantization errors of the feedback CSI. The proposed scheme controls its precoding parameters under a transmit power constraint by minimizing an upper bound of BER which is derived from the pairwise error probability and then averaged with respect to the CSI error. Computer simulations demonstrate that the proposed precoding method outperforms a conventional nonrobust MBER precoder and a conventional robust power allocation MBER precoder.

This paper proposes joint maximum a posteriori (MAP) detection and spatial filtering for MIMO-OFDM mobile communications, which can maintain excellent receiver performance even over interference-limited channels. The proposed joint processor consists of a log likelihood generator and a MAP equalizer. The log likelihood generator suppresses cochannel interference by spatially filtering received signals and provides branch metrics of transmitted signal candidates. Using the branch metrics, the MAP equalizer generates log likelihood ratios of coded bits and performs channel decoding based on the MAP criterion. In the first step, the log likelihood generator performs spatio-temporal filtering (STF) of the received signals prior to the fast Fourier transform (FFT) and is referred to as preFFT-type STF. For further improvement, in iterative steps, the generator performs spatial filtering (SF) of the received signals posterior to FFT and is referred to as postFFT-type SF. Estimation of both tap coefficients of the spatial filters and channel impulse responses employs the recursive least squares (RLS) with smoothing. The reason for making a switch from preFFT-type STF into postFFT-type SF is that preFFT-type STF outperforms postFFT-type SF with a limited number of preamble symbols while postFFT-type SF outperforms preFFT- type STF when data symbols can be reliably detected and used for the parameter estimation. Computer simulations demonstrate that the proposed joint processing can achieve excellent BER performance under interference-limited channel conditions and that it can outperform the conventional joint processing of preFFT-type STF and the MAP equalizer.

This paper proposes a new MIMO-OFDM preceding method that minimizes BER of the maximum likelihood detection (MLD). Conventional MIMO precoding methods can approximately minimize BER of the minimum mean square error (MMSE) based detector by using singular value decomposition (SVD) of the channel matrices. However, they cannot minimize BER of MLD because the orthogonalization does not increase the Euclidean distance between a pair of channel-distorted replicas of transmitted signals. To optimize the Euclidean distance effectively, the proposed method controls its precoding parameters by minimizing the upper bound of BER based on the pairwise error. Computer simulations demonstrate that the proposed precoding method outperforms the MMSE precoder and the conventional minimum BER (MBER) precoder that assumes the precoding matrix structure similar to the solution of the weighted MMSE precoder.

This paper proposes low-complexity blind detection for orthogonal frequency division multiplexing (OFDM) systems with the differential space-time block code (DSTBC) under time-varying frequency-selective Rayleigh fading. The detector employs the maximum likelihood sequence estimation (MLSE) in cooperation with the blind linear prediction (BLP), of which prediction coefficients are determined by the method of Lagrange multipliers. Interpolation of channel frequency responses is also applied to the detector in order to reduce the complexity. A complexity analysis and computer simulations demonstrate that the proposed detector can reduce the complexity to about a half, although it suffers a loss of 2.5 dB in Eb/N0at BER of 10-3owing to the complexity reduction when the prediction order and the degree of polynomial approximation are 2 and 1, respectively, with the normalized Doppler frequency of 1.6 times 10-2.

This paper proposes a new channel estimation method for the expectation-maximization (EM) algorithm applied to an OFDM receiver. Conventional schemes using the EM algorithm assume the random walk model as a process equation of a channel impulse response, and thus have insufficient tracking ability to fading fluctuation over fast fading channels. To improve the tracking ability, the proposed channel estimation method employs the differential model having the first and higher order differentials of the channel impulse response with respect to time. Computer simulations under the fast fading condition demonstrate that the proposed method is much superior in packet error rate to the conventional schemes employing the random walk model.

This paper proposes a MIMO-OFDM transmission scheme employing subcarrier-block phase hopping that can reduce peak-to-average power ratio (PAPR) while simultaneously improving transmission performance with low numerical complexity. As a conventional scheme for achieving these objectives, a combination of the enhanced selected mapping (ESLM) and the subcarrier phase hopping for space division multiplexing (SPH-SDM) has been proposed. To reduce the complexity furthermore and to increase feasibility of hardware implementation, the proposed scheme enhances SPH-SDM by introducing subcarrier-block phase hopping based on the partial transmit sequence (PTS). It divides the overall subcarriers into blocks and rotates phases of the complex signals which IFFT generates from the subcarriers of each block. Computer simulations demonstrate that the proposed scheme can drastically reduce PAPR and improve the packet error rate (PER) in comparison with the standard MIMO-OFDM, and that it can achieve almost the same performance as SPH-SDM with ESLM while achieving half as low complexity as that of the conventional one.

This paper proposes a maximum likelihood (ML) detector with spatial-temporal filters prewhitening cochannel interferences for MIMO-OFDM mobile communications. The proposed detector consists of several branch metric generators and an ML detector using metrics which the generators produce. In the branch metric generator, the spatial-temporal filter for received signals suppresses interfering signal components while prewhitening them. Subtracting replica signals from the filter's outputs and squaring the result yield the metrics. Coefficients of the filters and channel impulse responses for the replicas are estimated by using the eigenvalue decomposition (EVD) of an autocorrelation matrix of both the received and transmitted signals. To select appropriate eigenvectors for the branch metric generators, the proposed detector adopts a channel capacity criterion, and avoids prohibitive complexity by using a fast search algorithm. Another problem is that it requires a large amount of computational complexity for channel tracking because it performs parameter estimation using the nonrecursive EVD. To solve such a problem, the recursive EVD is applied, which can track the time-varying fading channel while simultaneously reducing the complexity. Computer simulations demonstrate that the proposed scheme can maintain an excellent BER performance in correlated channels and track the fast fading channel with reduced complexity.

This paper proposes a parallel recursive least square (P-RLS) channel estimator for the iterative maximum a posteriori (MAP) receiver. The targeted system is the low-density-parity-check (LDPC) coded multiple-input-multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) system. The proposed estimator, which can be theoretically derived from the message-passing algorithm, can track a fast fading channel, and allows the parallel implementation of the whole receiver. A simplified version of P-RLS (SP-RLS) that can reduce the computational complexity is also proposed. Compared to the RLS with smoothing and removing (SR-RLS), P-RLS can reduce the computational time by parallelization, and SP-RLS can further reduce the computational time and complexity. Computer simulations show that SP-RLS achieves almost the same packet error rate (PER) performance as that of P-RLS. It also achieves almost the same PER performance as that of SR-RLS with double iterations. Even in this case, the computational time and complexity of SP-RLS are smaller than those of SR-RLS.

This paper proposes novel channel estimation methods for an iterative maximum a posteriori (MAP) receiver. The targeted systems are low-density parity-check (LDPC)-coded multiple-input-multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) mobile communications. By reconsidering the joint processing of the iterative MAP receiver from the viewpoint of the message-passing algorithm in the factor graph, this paper theoretically derives the recursive least squares (RLS) algorithm with smoothing and removing (SR-RLS). The computational complexity of SR-RLS is about two to three times larger than that of the original RLS algorithm. Computer simulations under fast multipath fading conditions show that the MAP receiver using the proposed SR-RLS channel estimator outperforms the one using the conventional RLS channel estimator.

This paper proposes a new blind adaptive equalizer based on maximum-likelihood sequence estimation (MLSE) for frequency selective mobile radio channels. A conventional blind MLSE equalizer with a single fractionally spaced transversal filter can cope with timing offset, but it suffers from a performance degradation due to the ambiguity of blind channel estimation. To avoid this ambiguity, this paper proposes a different type of fractional sampling in which separate symbol-spaced channel estimations are performed in the respective fractional sampling phases. The estimation employs a recursive form using the Moore-Penrose generalized inverse matrix. The equalizer combines the separate channel estimation errors, and provides the sum for the Viterbi algorithm processor as the branch metric, which tremendously reduces the probability that the correct solution is turned into an ambiguous false solution. Computer simulation demonstrates the effectiveness of the proposed equalizer on frequency selective fading channels.

This paper proposes a MIMO-OFDM transmission scheme that combines the subcarrier phase hopping for space division multiplexing (SPH-SDM) with an enhanced selected mapping (ESLM). SPH-SDM randomizes the subcarrier phases within an OFDM symbol and makes subcarrier components of the received signal uncorrelated in order to improve BER performance of a MIMO-OFDM coded system. The phase patterns are adjusted so that they can not only randomize the subcarrier phase hopping but also reduce the peak-to-average power ratio (PAPR). In contrast to conventional PAPR reduction techniques for OFDM such as the selected mapping (SEM), ESLM employs roughly quantized IFFT processing for selecting the phase pattern in order to reduce the numerical complexity, and modulates the pilot subcarriers so as to inform the receiver of the selected phase pattern. Computer simulation shows that SPH-SDM with ESLM can increase the frequency diversity gain by channel coding, while simultaneously reducing PAPR by a suboptimum phase pattern

This paper proposes a suboptimal maximum likelihood detection (MLD) algorithm for multiple-input multiple-output (MIMO) communications. The proposed algorithm regards transmitted signals as continuous variables in the same way as a common method for the discrete optimization problem, and then searches candidates of the transmitted signals in the direction of a modified gradient vector of the metric. The vector enhances components in the gradient that are likely to cause the noise enhancement from which the zero-forcing (ZF) or minimum mean square error (MMSE) algorithms suffer. This method sets the initial guess to the solution by the ZF or MMSE algorithms, which can be recursively calculated. Also, the proposed algorithm requires the same complexity order as that of the ZF algorithm. Computer simulations demonstrate that it is superior in BER performance to conventional suboptimal algorithms of which complexity order is equal to that of ZF.

This paper proposes a maximum likelihood detection (MLD) method for the differential space-time block code (DSTBC) in cooperation with blind linear prediction (BLP) of fast frequency-flat fading channels. The method, which linearly predicts the fading complex envelope, determines the linear prediction coefficients by the method of Lagrange multipliers, and does not use decision-feedback nor require information on channel parameters such as the maximum Doppler frequency in contrast to conventional ones. Computer simulations under a fast fading condition demonstrate that the proposed method with a proper degree of polynomial approximation can be superior in BER performance to a conventional method that estimates the coefficients by the RLS algorithm using a training sequence.

This paper proposes two new types of maximum a posteriori probability (MAP) receivers for multiple-input-multiple-output and orthogonal frequency-division multiplexing mobile communications with a channel coding such as the low-density parity-check code. One proposed receiver employs the expectation-maximization algorithm so as to improve performance of approximated MAP detection. Differently from a conventional receiver employing the minimum mean-square estimation (MMSE) algorithm, it applies the recursive least squares (RLS) algorithm to the channel estimation in order to track a fast fading channel. For the purpose of further improvement, the other proposed receiver applies a new adaptive algorithm that can be derived from the message passing on factor graphs. The algorithm exploits all detected signals but one of targeted time, and can gain a considerable advantage over the MMSE and RLS. Computer simulations show that the first proposed receiver is superior in channel-tracking ability to the conventional receiver employing the MMSE. Furthermore, it is demonstrated that the second proposed receiver remarkably outperforms both the conventional and the first proposed ones.

This paper proposes a new blind algorithm effective for multiuser detection with an adaptive array antenna. The conventional blind algorithm, known as the constant modulus algorithm (CMA), has two major drawbacks: (i) the convergence speed is not sufficiently fast for usual applications in mobile communications, and (ii) the algorithm is very likely to lock on the path with the largest received power, which means the signal with the second largest power can hardly be extracted. This paper introduces the recursive least squares algorithm for CMA (RLS-CMA) in order to speed the convergence up, and additionally introduces the concept of the orthogonal projection into CMA so as to extract signals with weak power. The proposed CMA with orthogonal projection (CMA-OP) sequentially calculates the weight vector of each user under a constraint that the weight vector should be orthogonal to the estimated array response vectors of previously extracted users. Computer simulation demonstrates that the proposed scheme can operate properly in the Rayleigh fading channels under the two-user condition.

This paper proposes a frame synchronization method for adaptive array antennas (AAA) in digital mobile communications, which can achieve excellent performance even in severe asynchronous co-channel interference environments, in contrast to the conventional correlator-based methods. The proposed scheme that is based on maximum a posteriori (MAP) estimation utilizes the AAA's outputs of which interference signal components are drastically suppressed. Computer simulations show that the proposed scheme can operate properly even in interference-rich fading environments, and that it can significantly improve the synchronization performance.

This paper proposes a new correction technique for the LInear amplification with Nonlinear Components (LINC) transmitters. The technique, which is based on the minimum mean squared error (MMSE) criterion, estimates the gain and phase imbalance between the two amplifier branches. With information on the estimation, the imbalance is compensated by controlling the amplitude and phase of the input signal that is fed into one of the two amplifiers. Computer simulations with the QPSK modulation demonstrate that this method can calibrate the balance and sufficiently suppress the out-of-band distortion spectra.

This paper proposes a new maximum likelihood OFDM receiver for multipath fading environment with large delay spread. The large delay difference over the guard interval (GI) duration of the OFDM signal generally results in intersymbol interference (ISI) between temporally adjacent symbols and interchannel interference (ICI). Both of them spread over a large number of subcarriers. The new OFDM receiver consists of equalizers for both ISI and ICI and an accurate channel impulse response estimator. Furthermore, it introduces a temporal-window technique for the FFT-window in order to suppress the ICI, which is very effective for reducing the complexity of ICI equalization by maximum likelihood sequence estimator (MLSE). Computer simulation is conducted in order to verify the performance of the proposed OFDM receiver, and its effectiveness is shown.

This paper proposes an interference cancellation technique for DS-CDMA downlink mobile communication systems. The proposed scheme, referred to as orthogonal successive interference canceller (OSIC), is a low complexity version of the decorrelating decision-feedback detector (DDFD) proposed by Duel-Hallen (1993), which is achieved by using an orthogonal filter bank. A lower complexity scheme that takes into consideration only the subset of strongest active users at the OSIC is also proposed. For coherent detection of the OSIC under fading channels, the fixed AR model predictive and the higher order predictive channel estimation are employed. Computer simulations show that the proposed schemes with these two channel estimation techniques can achieve excellent BER performances under both AWGN and flat Rayleigh fading channels.