No Arabic abstract
We propose a three-track detection system for two dimensional magnetic recording (TDMR) in which a local area influence probabilistic (LAIP) detector works with a trellis-based Bahl-Cocke-Jelinek-Raviv (BCJR) detector to remove intersymbol interference (ISI) and intertrack interference (ITI) among coded data bits as well as media noise due to magnetic grain-bit interactions. Two minimum mean-squared error (MMSE) linear equalizers with different response targets are employed before the LAIP and BCJR detectors. The LAIP detector considers local grain-bit interactions and passes coded bit log-likelihood ratios (LLRs) to the channel decoder, whose output LLRs serve as a priori information to the BCJR detector, which is followed by a second channel decoding pass. Simulation results under 1-shot decoding on a grain-flipping-probability (GFP) media model show that the proposed LAIP/BCJR detection system achieves density gains of 6.8% for center-track detection and 1.2% for three-track detection compared to a standard BCJR/1D-PDNP. The proposed systems BCJR detector bit error rates (BERs) are lower than those of a recently proposed two-track BCJR/2D-PDNP system by factors of (0.55, 0.08) for tracks 1 and 2 respectively.
In this paper, we investigate the sequence estimation problem of faster-than-Nyquist (FTN) signaling as a promising approach for increasing spectral efficiency (SE) in future communication systems. In doing so, we exploit the concept of Gaussian separability and propose two probabilistic data association (PDA) algorithms with polynomial time complexity to detect binary phase-shift keying (BPSK) FTN signaling. Simulation results show that the proposed PDA algorithm outperforms the recently proposed SSSSE and SSSgb$K$SE algorithms for all SE values with a modest increase in complexity. The PDA algorithm approaches the performance of the semidefinite relaxation (SDRSE) algorithm for SE values of $0.96$ bits/sec/Hz, and it is within the $0.5$ dB signal-to-noise ratio (SNR) penalty at SE values of $1.10$ bits/sec/Hz for the fixed values of $beta = 0.3$.
In this paper, we reconsider the problem of detecting a matrix-valued rank-one signal in unknown Gaussian noise, which was previously addressed for the case of sufficient training data. We relax the above assumption to the case of limited training data. We re-derive the corresponding generalized likelihood ratio test (GLRT) and two-step GLRT (2S--GLRT) based on certain unitary transformation on the test data. It is shown that the re-derived detectors can work with low sample support. Moreover, in sample-abundant environments the re-derived GLRT is the same as the previously proposed GLRT and the re-derived 2S--GLRT has better detection performance than the previously proposed 2S--GLRT. Numerical examples are provided to demonstrate the effectiveness of the re-derived detectors.
Recently, several array radar structures combined with sub-Nyquist techniques and corresponding algorithms have been extensively studied. Carrier frequency and direction-of-arrival (DOA) estimations of multiple narrow-band signals received by array radars at the sub-Nyquist rates are considered in this paper. We propose a new sub-Nyquist array radar architecture (a binary array radar separately connected to a multi-coset structure with M branches) and an efficient joint estimation algorithm which can match frequencies up with corresponding DOAs. We further come up with a delay pattern augmenting method, by which the capability of the number of identifiable signals can increase from M-1 to Q-1 (Q is extended degrees of freedom). We further conclude that the minimum total sampling rate 2MB is sufficient to identify $ {K leq Q-1}$ narrow-band signals of maximum bandwidth $B$ inside. The effectiveness and performance of the estimation algorithm together with the augmenting method have been verified by simulations.
Probabilistic shaping (PS) is a promising technique to approach the Shannon limit using typical constellation geometries. However, the impact of PS on the chain of signal processing algorithms of a coherent receiver still needs further investigation. In this work we study the interplay of PS and phase recovery using the blind phase search (BPS) algorithm, which is widely used in optical communications systems. We first investigate a supervised phase search (SPS) algorithm as a theoretical upper bound on the BPS performance, assuming perfect decisions. It is shown that PS influences the SPS algorithm, but its impact can be alleviated by moderate noise rejection window sizes. On the other hand, BPS is affected by PS even for long windows because of correlated erroneous decisions in the phase recovery scheme. The simulation results also show that the capacity-maximizing shaping is near to the BPS worst-case situation for square-QAM constellations, causing potential implementation penalties.
In this paper, we propose a novel wireless architecture, mounted on a high-altitude aerial platform, which is enabled by reconfigurable intelligent surface (RIS). By installing RIS on the aerial platform, rich line-of-sight and full-area coverage can be achieved, thereby, overcoming the limitations of the conventional terrestrial RIS. We consider a scenario where a sudden increase in traffic in an urban area triggers authorities to rapidly deploy unmanned-aerial vehicle base stations (UAV- BSs) to serve the ground users. In this scenario, since the direct backhaul link from the ground source can be blocked due to several obstacles from the urban area, we propose reflecting the backhaul signal using aerial-RIS so that it successfully reaches the UAV-BSs. We jointly optimize the placement and array-partition strategies of aerial-RIS and the phases of RIS elements, which leads to an increase in energy-efficiency of every UAV-BS. We show that the complexity of our algorithm can be bounded by the quadratic order, thus implying high computational efficiency. We verify the performance of the proposed algorithm via extensive numerical evaluations and show that our method achieves an outstanding performance in terms of energy-efficiency compared to benchmark schemes.