This paper proposes a novel interference cancellation technique that prevents radio receivers from degrading due to periodic interference signals caused by electromagnetic waves emitted from high power circuits. The proposed technique cancels periodic interference signals in the frequency domain, even if the periodic interference signals drift in the time domain. We propose a drift estimation based on a super resolution technique such as ESPRIT. Moreover, we propose a sequential drift estimation to enhance the drift estimation performance. The proposed technique employs a linear filter based on the minimum mean square error criterion with assistance of the estimated drifts for the interference cancellation. The performance of the proposed technique is confirmed by computer simulation. The proposed technique achieves a gain of more than 40dB at the higher frequency part in the band. The proposed canceler achieves such superior performance, if the parameter sets are carefully selected. The proposed sequential drift estimation relaxes the parameter constraints, and enables the proposed cancellation to achieve the performance upper bound.

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.

In this paper, an adaptive expansion strategy (AES) is proposed for multiple-input/multiple-output (MIMO) detection in the presence of circular signals. By exploiting channel properties, the AES classifies MIMO channels into three types: excellent, average and deep fading. To avoid unnecessary branch-searching, the AES adopts single expansion (SE), partial expansion (PE) and full expansion (FE) for excellent channels, average channels and deep fading channels, respectively. In the PE, the non-circularity of signal is exploited, and the widely linear processing is extended from non-circular signals to circular signals by I (or Q) component cancellation. An analytical performance analysis is given to quantify the performance improvement. Simulation results show that the proposed algorithm can achieve quasi-optimal performance with much less complexity (hundreds of flops/symbol are saved) compared with the fixed-complexity sphere decoder (FSD) and the sphere decoder (SD).

Novel joint motion-compensated interpolation using eight-neighbor block motion vectors (8J-MCI) is presented. The proposed method uses bi-directional motion estimation (BME) to obtain the motion vector field of the interpolated frame and adopts motion vectors of the interpolated block and its 8-neighbor blocks to jointly predict the target block. Since the smoothness of the motion vector filed makes the motion vectors of 8-neighbor blocks quite close to the true motion vector of the interpolated block, the proposed algorithm has the better fault-tolerancy than traditional ones. Experiments show that the proposed algorithm outperforms the motion-aligned auto-regressive algorithm (MAAR, one of the state-of-the-art frame rate up-conversion (FRUC) schemes) in terms of the average PSNR for the test image sequence and offers better subjective visual quality.

In this paper, the issue of carrier frequency offset (CFO) compensation in interleaved orthogonal frequency division multiple access (OFDMA) uplink system is investigated. To mitigate the effect of multiple access interference (MAI) caused by CFOs of different users, a new parallel interference cancellation (PIC) compensation algorithm is proposed. This scheme uses minimum mean square error (MMSE) criterion to obtain the estimation of interference users, then circular convolutions are employed to restore MAI and compensate CFO. To tackle the complexity problem of circular convolutions, an efficient MAI restoration and cancellation method is developed. Simulations illustrate the good performance and low computational complexity of the proposed algorithm.

In this letter, a new joint precoding and decoding design scheme for multiuser MIMO downlink is proposed which dispenses with iterative operations and can achieve better performance. This scheme introduces zero-force processing into minimum mean square error (MMSE) design scheme to avoid iterative operations. We derived closed-form precoders and decoders and transmit power allocation strategy of proposed design scheme, validated performance of proposed design scheme by computer simulation. The simulation results show that the proposed design scheme can achieve better bit error rate (BER) and sum capacity performance compared to an existing non-iterative design scheme.

In this paper, a non-data aided minimum mean square error (MMSE) receiver with enhanced multiple access interference (MAI) suppression is proposed for direct-sequence code-division multiple-access (DS-CDMA) systems over a multipath fading channel. The design of the proposed receiver is via the following procedure: First, an adaptive correlator is constructed based on the linearly constrained minimum variance (LCMV) criterion to collect each multipath signal and suppress MAI blindly. A maximum ratio combiner is then utilized to coherently combine the correlator outputs. With a set of judicious chosen weight vectors, effective diversity combining can successfully suppress MAI and the desired signals can be effectively retained. Finally, further performance improvement against the finite data sample effect is achieved using a decision-aided scheme in which the channel response is obtained by the decision data and incorporated with the MMSE method to compute the refined weight vector. Performance analysis based on the output signal-to-interference-plus-noise ratio (SINR) is done to examine the efficacy of the proposed non-data aided MMSE receiver, which can offer the similar results as those of the MMSE receiver with the channel estimation correctly obtained beforehand. Computer simulation results then confirm correctness of the analysis results and demonstrate that the proposed blind receiver can successfully resist MAI as well as the finite data sample effect, and significantly outperform than the conventional blind receivers.