An iterative inter-track interference (ITI) cancelling scheme is described for multi-track signal detection in nonbinary (NB)-LDPC-coded two-dimensional magnetic recording. The multi-track iterative ITI canceller that we propose consists of multi-track soft interference cancellers (SICs), two-dimensional partial response (TDPR) filters, noise-predictive max-log-MAP detectors, and an NB-LDPC decoder. TDPR filters using an ITI-suppressing tap-weight vector mitigate ITI in the first iteration. Multi-track SICs and TDPR filters adjusted to the residual two-dimensional ISI signals efficiently detect multi-track signals in the latter iterations. The simulation results demonstrated that our proposed iterative multi-track ITI canceller achieves frame error rates close to those obtained in a non-ITI case in media-noise-dominant environments when the both-side off-track ratio is up to 50%.

In multiple-input multiple-output (MIMO) wireless systems, the receiver must extract each transmitted signal from received signals. Iterative signal detection with belief propagation (BP) can improve the error rate performance, by increasing the number of detection and decoding iterations in MIMO systems. This number of iterations is, however, limited in actual systems because each additional iteration increases latency, receiver size, and so on. This paper proposes a convergence acceleration technique that can achieve better error rate performance with fewer iterations than the conventional iterative signal detection. Since the Log-Likelihood Ratio (LLR) of one bit propagates to all other bits with BP, improving some LLRs improves overall decoder performance. In our proposal, all the coded bits are divided into groups and only one group is detected in each iterative signal detection whereas in the conventional approach, each iterative signal detection run processes all coded bits, simultaneously. Our proposal increases the frequency of initial LLR update by increasing the number of iterative signal detections and decreasing the number of coded bits that the receiver detects in one iterative signal detection. Computer simulations show that our proposal achieves better error rate performance with fewer detection and decoding iterations than the conventional approach.

To improve the channel estimation accuracy of multiple-input multiple-output (MIMO) multiplexing, we previously proposed iterative QR-decomposition with M-algorithm (QRD-M) with decision directed channel estimation. In this paper, to keep the computational complexity low while further improving the transmission performance, we will modify previously proposed iterative QRD-M by incorporating cyclic redundancy check (CRC) coding. In the proposed method, transmitted signals are ranked according to their results of CRC decoding and the received signal-to-interference plus noise power ratio (SINR). In the modified M-algorithm, since the results of Turbo decoding and CRC decoding are used to generate the surviving symbol replica, the accuracy of signal detection in the following steps can be improved. Furthermore, based on the results of CRC decoding, iterative process can be terminated before reaching the maximum allowable number of iterations. Computer simulation results show that the loss in the required average received signal energy per bit-to-noise power spectrum density ratio Eb/N0 for average packet error rate (PER) = 10-2 is only about 0.4 dB from maximum likelihood detection (Full MLD) with ideal channel estimation.