In this paper, we study the achievable degrees of freedom (DoF) of a multiple-input multiple-output (MIMO) multi-way relay channel with asymmetric message set that models the scenario of the two-way communication between a base station and multiple users through a relay. Under the assumption of delayed channel state information at transmitters (CSIT), we propose an amplify-and-forward relaying scheme based on the scheme proposed by Maddah-Ali and Tse to support signal space alignment, so that the available dimensions of the signal spaces at the relay and the users can be efficiently utilized. The proposed scheme outperforms the traditional one-way scheme from the perspective of DoF, and is useful to relieve the communication bottleneck caused by the asymmetric traffic load inherent in cellular networks.

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

A multi-phase crystal-less clock generator (MPCLCG) with a process-voltage-temperature (PVT) calibration circuit is proposed. It operates at 192 MHz with 8 phases outputs, and is implemented as a 0.18µm CMOS process for digital power management systems. A temperature calibrated circuit is proposed to align operational frequency under process and supply voltage variations. It occupies an area of 65µm × 75µm and consumes 1.1mW with the power supply of 1.8V. Temperature coefficient (TC) is 69.5ppm/°C from 0 to 100°C, and 2-point calibration is applied to calibrate PVT variation. The measured period jitter is a 4.58-ps RMS jitter and a 34.55-ps peak-to-peak jitter (P2P jitter) at 192MHz within 12.67k-hits. At 192MHz, it shows a 1-MHz-offset phase noise of -102dBc/Hz. Phase to phase errors and duty cycle errors are less than 5.5% and 4.3%, respectively.

Faster-than-Nyquist (FTN) signaling is investigated for quasi-static flat fading massive multiple-input multiple-output (MIMO) systems. In FTN signaling, pulse trains are sent at a symbol rate higher than the Nyquist rate to increase the transmission rate. As a result, inter-symbol interference occurs inevitably for flat fading channels. This paper assesses the information-theoretically achievable rate of MIMO FTN signaling based on the optimum joint equalization and multiuser detection. The replica method developed in statistical physics is used to evaluate the achievable rate in the large-system limit, where the dimensions of input and output signals tend to infinity at the same rate. An analytical expression of the achievable rate is derived for general modulation schemes in the large-system limit. It is shown that FTN signaling does not improve the channel capacity of massive MIMO systems, and that FTN signaling with quadrature phase-shift keying achieves the channel capacity for all signal-to-noise ratios as the symbol period tends to zero.

Reliable wireless communication often requires accurate knowledge of the underlying multipath channels. Numerous measurement campaigns have shown that physical multipath channels tend to exhibit a sparse structure. Conventional blind channel identification (BCI) strategies such as the least squares, which are known to be optimal under the assumption of rich multipath channels, are ill-suited to exploiting the inherent sparse nature of multipath channels. Recently, l1-norm regularized least-squares-type approaches have been proposed to address this problem with a single parameter governing all coefficients, which is equivalent to maximum a posteriori probability estimation with a Laplacian prior for the channel coefficients. Since Laplace prior is not conjugate to the Gaussian likelihood, no closed form of Bayesian inference is possible. Following a different approach, this paper deals with blind channel identification of a single-input multiple-output (SIMO) system based on sparse Bayesian learning (SBL). The inherent sparse nature of wireless multipath channels is exploited by incorporating a transformative cross relation formulation into a general Bayesian framework, in which the filter coefficients are governed by independent scalar parameters. A fast iterative Bayesian inference method is then applied to the proposed model for obtaining sparse solutions, which completely eliminates the need for computationally costly parameter fine tuning, which is necessary in the l1-norm regularization method. Simulation results are provided to demonstrate the superior effectiveness of the proposed channel estimation algorithm over the conventional least squares (LS) scheme as well as the l1-norm regularization method. It is shown that the proposed algorithm exhibits superior estimation performance compared to both LS and l1-norm regularization methods.

In this paper, an iterative robust minimum-mean square error (MMSE) receiver for space-time block coding (STBC) is proposed to mitigate the performance degradations caused by channel state information (CSI) errors. The proposed scheme estimates an instantaneous covariance matrix of the effective noise, which includes additive white Gaussian noise and the effect of CSI errors. For this estimation, multiple solution candidate vectors are selected based on the distances between the MMSE estimate of the solution and the constellation points, and their a-posteriori probabilities are utilized to execute the estimation of the covariance matrix. To improve the estimation accuracy, the estimated covariance matrix is updated iteratively. Simulation results show that proposed robust receiver achieves substantial performance gains in terms of bit error rates as compared to conventional receiver schemes under CSI errors.

Authors have studied degradation phenomenon on electrical contacts under the influences of an external micro-oscillation. A new micro-sliding mechanism 2 (MSM2) has developed, which provides micro-sliding driven by a piezo-electric actuator and elastic hinges. The experimental results are obtained on “minimal sliding amplitudes” to make resistances fluctuate on electrical contacts under some conditions which are three types of inputwaveform (sinusoidal, rectangular, and impulsive) and three levels of frictional force (1.6, 1.0, and 0.3 N/pin) by using the MSM2. The dynamical characteristics are discussed under the conditions. The simple theoretical model on the input signal and the output of the mechanism is built and the theoretical expressions from the model are obtained. A natural angular frequency (ω0=12600[s-1]) and a damping ratio (ζ=0.03[-]) are evaluated using experimental dynamical responses. The waveforms of inputs and outputs are obtained and the characteristics between inputs and outputs are also obtained on the theoretical model using the above. The maximal gain between the input and the output in rectangular or impulsive (24.4) is much larger than that (0.0) in sinusoidal. The difference on the output-accelerations between in sinusoidal and in rectangular (impulsive) is discussed. It is shown that it is possible to cause the degradation phenomenon in sinusoidal only when the output displacement are enlarged. It is also shown that it is possible to cause the phenomenon in rectangular or in impulsive, in addition to the above, when the external force has sharper rising and falling waveforms even if the displacement and the frequency of the force is small. The difference on the output-amplitudes between in rectangular and in impulsive is discussed. It is not clear that there is the difference between the effect in rectangular and that in impulsive. It is indicated that it is necessary to discuss the other causes, for instance, another dynamical, thermal, and chemical process.

This paper presents an adaptive interference-aware receiver for multiuser multiple-input multiple-output (MU-MIMO) downlink systems in wireless local area network (WLAN) systems. The MU-MIMO downlink technique is one of the key techniques that are newly applied to WLAN systems in order to support a very high throughput. However, the simultaneous communication of several users causes inter-user interference (IUI), which adversely affects receivers. Therefore, in order to prevent IUI, a precoding technique is defined at the transmitter based on feedback from the receiver. Unfortunately, however, the receiver still suffers from interference, because the precoding technique is prone to practical errors from the feedback quantization and subcarrier grouping scheme. Whereas ordinary detection schemes are available to mitigate such interference, such schemes are unsuitable because of their low performance or high computational complexity. In this paper, we propose an switching algorithm based on the norm ratio between an effective channel matrix for the desired signal and that of the interfering signals. Simulation results based on the IEEE 802.11ac standard show that the proposed algorithm can achieve near-optimal performance with a 70% reduction in computational complexity.

In this letter, we propose a lattice reduction (LR) aided joint precoding design for MIMO-relay broadcast communication with the average bit error rate (BER) criterion. We jointly design the signal process flow at both the base station (BS), and the relay station (RS), using the reduced basis of two-stage channel matrices. We further modify the basic precoding design with a novel shift method and a modulo method to improve the power efficiency at the BS and the RS respectively. In addition, the MMSE-SIC algorithm is employed to improve the performance of precoding. Simulations show that, the proposed schemes achieve higher diversity order than the traditional precoding without LR, and the modified schemes significantly outperform the basic design, proving the effectiveness of the proposed methods.

A design scheme for a high-speed differential-input limiting transimpedance amplifier (TIA) was developed. The output-stage amplifier of the TIA is investigated in detail in order to suppress undershoot and ringing in the output waveform. The amplifier also includes a peak detector for the received signal strength indicator (RSSI) output, which is used to control the optical demodulator for differential-phase-shift-keying or differential-quadrature-phase-shift-keying formats. The limiting TIA was fabricated on the basis of 1-µm emitter-width InP-based heterojunction-bipolar-transistor (HBT) IC technology. Its differential gain is 39 dB, its 3-dB bandwidth is 27 GHz, and its estimated differential transimpedance gain is 73 dBΩ. The obtained output waveform shows that the developed design scheme is effective for suppressing undershoot and ringing.

We consider a bisimilarity control problem for transition systems. For this control problem, a necessary and sufficient condition for its solvability and a method for synthesizing a state feedback controller have been presented in the literature. However, the state of the system to be controlled is not necessarily observable. In this paper, we synthesize an observer-based output feedback controller for the bisimilarity control problem under a certain condition, and show that this output feedback controller is a solution to the control problem.

Recent development in network technology can realize the control of a remote plant by a digital controller. However, there is a delay caused by data transmission of control inputs and outputs. The delay degrades the control performance without taking it into consideration. In general, it is a difficult problem to identify the delay beforehand. We also assume that the plant's parameters have uncertainty. To solve the problem, we use reinforcement learning to achieve optimal digital control. First, we consider state feedback control. Next, we consider the case where the plant's outputs are observed, and apply reinforcement learning to output feedback control. Finally, we demonstrate by simulation that the proposed control method can search for the optimal gain and that it can adapt to the change of the delay.

The feasibility condition of interference alignment (IA) for multiple-input multiple-output two-way interference channel is studied in this paper. A necessary condition and a sufficient condition on the IA feasibility are established and the sum degrees of freedom (DoF) for a broad class of network topologies is characterized. The numerical results demonstrate that two-way operation with appropriate IA is able to achieve larger sum DoF than the conventional one-way operation.

This paper explores the potential of pitch determination from bone conducted (BC) speech. Pitch determination from normal air conducted (AC) speech signal can not attain the expected level of accuracy for every voice and background conditions. In contrast, since BC speech is caused by the vibrations that have traveled through the vocal tract wall, it is robust against ambient conditions. Though an appropriate model of BC speech is not known, it has regular harmonic structure in the lower spectral region. Due to this lowpass nature, pitch determination from BC speech is not usually affected by the dominant first formant. Experiments conducted on simultaneously recorded AC and BC speech show that BC speech is more reliable for pitch estimation than AC speech. With little human work, pitch contour estimated from BC speech can also be used as pitch reference that can serve as an alternate to the pitch contour extracted from laryngograph output which is sometimes inconsistent with simultaneously recorded AC speech.

This paper presents a codeword metric calculation scheme for two step joint decoding of block coded signals in overloaded multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. A two step joint decoding scheme has been proposed for the complexity reduction as compared to joint maximum likelihood decoding in overloaded MIMO systems. Outer codes are widely used in wireless LANs such as IEEE802.11n. However, the two step joint decoding has not been combined with an outer code. In the first step of the two step joint decoding candidate codewords for metric calculation in the second step are selected. The selection of the candidate codewords in the inner block code may not always be able to provide the metric of a binary coded symbol for the outer code. Moreover, a bit flipping based codeword selection scheme in the two step joint decoding may not always provide the second best candidate codeword. Thus, in the proposed scheme the metric of the binary coded symbol calculated in the first step is reused in the second step of two step joint decoding. It is shown that the two step joint decoding with the proposed metric calculation scheme achieves better performance than that of the joint decoding with the bit flipping based codeword calculation scheme and reduces the complexity by about 0.013 for 4 signal streams with the cost of bit error rate degradation within 0.5dB.

We consider a chain of integrators system that has an uncertain delay in the input. Also, there is a measurement noise in the feedback channel that only noisy output is available. We develop a new output feedback control scheme along with amplification such that the ultimate bounds of all states and output of the controlled system can be made arbitrarily small. We note that the condition imposed on the sensor noise is quite general over the existing results such that the sensor noise is uncertain and is only required to be bounded by a known bound. The benefit of our control method is shown via an example.

The capacity maximization of line-of-sight (LoS) two-input and multiple-output (TIMO) channels in indoor environments is investigated in this paper. The 3×2 TIMO channel is mainly studied. First, the capacity fluctuation number (CFN) which reflects the variation of channel capacity is proposed. Then, the expression of the average capacity against the CFN is derived. The CFN is used as a criterion for optimization of the capacity by changing inter-element spacings of transmit and receive antenna arrays. Next, the capacity sensitivity of the 3×2 TIMO channel to the orientation and the frequency variation is studied and compared with those of 2×2 and 4×2 TIMO channels. A small capacity sensitivity of the 3×2 TIMO channel is achieved and verified by both simulation and measurement results. Furthermore, the CFN can also be used as a criterion for optimization of average capacity and the proposed optimization method is validated through numerical results.

This paper proposes a novel iterative multiple-input multiple-output (MIMO) receiver for orthogonal frequency division multiplexing (OFDM) systems, named as an “iterative MIMO receiver employing virtual channels with a Turbo decoder.” The proposed MIMO receiver comprises a MIMO detector with virtual channel detection and a Turbo decoder, between which signals are exchanged iteratively. This paper proposes a semi hard input soft output (SHISO) iterative decoding for the iterative MIMO receiver that achieves better performance than a soft input soft output (SISO) iterative decoding. Moreover, this paper proposes a new criterion for the MIMO detector to select the most likely virtual channel. The performance of the proposed receiver is verified in a 6×2 MIMO-OFDM system by computer simulation. The proposed receiver achieves better performance than the SISO MAP iterative receiver by 1.5dB at the bit error rate (BER) of 10-4, by optimizing the number of the Turbo iteration per the SHISO iteration. Moreover, the proposed detection criterion enables the proposed receiver to achieve a gain of 3.0dB at the BER of 10-5, compared with the SISO MAP iterative receiver with the Turbo decoder.

Implicit feedback is an approach that utilizes uplink channel state information (CSI) for downlink transmit beamforming on multiple-input multiple-output (MIMO) systems, relying on over-the-air channel reciprocity. The implicit feedback improves throughput efficiency because overhead of CSI feedback for change of over-the-air channel responses is omitted. However, it is necessary for the implicit feedback to calibrate circuitry responses that uplink CSI includes, because actual downlink and uplink channel responses do not match due to different transmit and receive circuitry chains. This paper presents our proposed calibration scheme, weighted-combining calibration (WCC); it offers improved calibration accuracy. In WCC, an access point (AP) calculates multiple calibration coefficients from ratios of downlink and uplink CSI, and then combines coefficients with minimum mean square error (MMSE) weights. The weights are derived using a linear approximation in the high signal to noise power ratio (SNR) regime. Analytical mean square error (MSE) of calibration coefficients with WCC and calibration schemes for comparison is expressed based on the linear approximation. Computer simulations show that the analytical MSE matches simulated one if the linear approximation holds, and that WCC improves the MSE and signal to interference plus noise power ratio (SINR). Indoor experiments are performed on a multiuser MIMO system with implicit feedback based on orthogonal frequency division multiplexing (OFDM), built using measurement hardware. Experimental results verify that the channel reciprocity can be exploited on the developed multiuser MIMO-OFDM system and that WCC is also effective in indoor environments.

This paper presents a downlink interference mitigation framework for two-tier heterogeneous networks, that consist of spectrum-sharing macrocells and femtocells*. This framework establishes cooperation between the two tiers through two algorithms, namely, the restricted waterfilling (RWF) algorithm and iterative reweighted least squares interference alignment (IRLS-IA) algorithm. The proposed framework models the macrocell-femtocell two-tier cellular system as an overlay cognitive radio system in which the macrocell system plays the role of the primary user (PU) while the femtocell networks play the role of the cognitive secondary users (SUs). Through the RWF algorithm, the macrocell basestation (MBS) cooperates with the femtocell basestations (FBSs) by releasing some of its eigenmodes to the FBSs to do their transmissions even if the traffic is heavy and the MBS's signal to noise power ratio (SNR) is high. Then, the FBSs are expected to achieve a near optimum sum rate through employing the IRLS-IA algorithm to mitigate both the co-tier and cross-tier interference at the femtocell users' (FUs) receivers. Simulation results show that the proposed IRLS-IA approach provides an improved sum rate for the femtocell users compared to the conventional IA techniques, such as the leakage minimization approach and the nuclear norm based rank constraint rank minimization approach. Additionally, the proposed framework involving both IRLS-IA and RWF algorithms provides an improved total system sum rate compared with the legacy approaches for the case of multiple femtocell networks.