27,429 research outputs found
Joint data detection and channel estimation for OFDM systems
We develop new blind and semi-blind data detectors and channel estimators for orthogonal frequency-division multiplexing (OFDM) systems. Our data detectors require minimizing a complex, integer quadratic form in the data vector. The semi-blind detector uses both channel correlation and noise variance. The quadratic for the blind detector suffers from rank deficiency; for this, we give a low-complexity solution. Avoiding a computationally prohibitive exhaustive search, we solve our data detectors using sphere decoding (SD) and V-BLAST and provide simple adaptations of the SD algorithm. We consider how the blind detector performs under mismatch, generalize the basic data detectors to nonunitary constellations, and extend them to systems with pilots and virtual carriers. Simulations show that our data detectors perform well
MIMO-aided near-capacity turbo transceivers: taxonomy and performance versus complexity
In this treatise, we firstly review the associated Multiple-Input Multiple-Output (MIMO) system theory and review the family of hard-decision and soft-decision based detection algorithms in the context of Spatial Division Multiplexing (SDM) systems. Our discussions culminate in the introduction of a range of powerful novel MIMO detectors, such as for example Markov Chain assisted Minimum Bit-Error Rate (MC-MBER) detectors, which are capable of reliably operating in the challenging high-importance rank-deficient scenarios, where there are more transmitters than receivers and hence the resultant channel-matrix becomes non-invertible. As a result, conventional detectors would exhibit a high residual error floor. We then invoke the Soft-Input Soft-Output (SISO) MIMO detectors for creating turbo-detected two- or three-stage concatenated SDM schemes and investigate their attainable performance in the light of their computational complexity. Finally, we introduce the powerful design tools of EXtrinsic Information Transfer (EXIT)-charts and characterize the achievable performance of the diverse near- capacity SISO detectors with the aid of EXIT charts
Single-RF spatial modulation requires single-carrier transmission: frequency-domain turbo equalization for dispersive channels
In this paper, we propose a broadband single-carrier (SC) spatial-modulation (SM) based multiple-input multipleoutput (MIMO) architecture relying on a soft-decision (SoD) frequency-domain equalization (FDE) receiver. We demonstrate that conventional orthogonal frequency-division multiplexing (OFDM)-based broadband transmissions are not readily suitable for the single–radio frequency (RF) assisted SM-MIMO schemes, since this scheme does not exhibit any substantial performance advantage over single-antenna transmissions. To circumvent this limitation, a low-complexity soft-decision (SoD) FDE algorithm based on the minimum mean-square error (MMSE) criterion is invoked for our broadband SC-based SM-MIMO scheme, which is capable of operating in a strongly dispersive channel having a long channel impulse response (CIR) at a moderate decoding complexity. Furthermore, our SoD FDE attains a near-capacity performance with the aid of a three-stage concatenated SC-based SM architecture
Information Storage and Retrieval for Probe Storage using Optical Diffraction Patterns
A novel method for fast information retrieval from a probe storage device is
considered. It is shown that information can be stored and retrieved using the
optical diffraction patterns obtained by the illumination of a large array of
cantilevers by a monochromatic light source. In thermo-mechanical probe
storage, the information is stored as a sequence of indentations on the polymer
medium. To retrieve the information, the array of probes is actuated by
applying a bending force to the cantilevers. Probes positioned over
indentations experience deflection by the depth of the indentation, probes over
the flat media remain un-deflected. Thus the array of actuated probes can be
viewed as an irregular optical grating, which creates a data-dependent
diffraction pattern when illuminated by laser light. We develop a low
complexity modulation scheme, which allows the extraction of information stored
in the pattern of indentations on the media from Fourier coefficients of the
intensity of the diffraction pattern. We then derive a low-complexity maximum
likelihood sequence detection algorithm for retrieving the user information
from the Fourier coefficients. The derivation of both the modulation and the
detection schemes is based on the Fraunhofer formula for data-dependent
diffraction patterns. We show that for as long as the Fresnel number F<0.1, the
optimal channel detector derived from Fraunhofer diffraction theory does not
suffer any significant performance degradation.Comment: 14 pages, 11 figures. Version 2: minor misprints corrected,
experimental section expande
Generalized feedback detection for spatial multiplexing multi-antenna systems
We present a unified detection framework for spatial multiplexing multiple-input multiple-output (MIMO) systems by generalizing Heller’s classical feedback decoding algorithm for convolutional codes. The resulting generalized feedback detector (GFD) is characterized by three parameters: window size, step size and branch factor. Many existing MIMO detectors are turned out to be special cases of the GFD. Moreover, different parameter choices can provide various performance-complexity tradeoffs. The connection between MIMO detectors and tree search algorithms is also established. To reduce redundant computations in the GFD, a shared computation technique is proposed by using a tree data structure. Using a union bound based analysis of the symbol error rates, the diversity order and signal-to-noise ratio (SNR) gain are derived analytically as functions of the three parameters; for example, the diversity order of the GFD varies between 1 and N. The complexity of the GFD varies between those of the maximum-likelihood (ML) detector and the zero-forcing decision feedback detector (ZFDFD). Extensive computer simulation results are also provided
A Scalable VLSI Architecture for Soft-Input Soft-Output Depth-First Sphere Decoding
Multiple-input multiple-output (MIMO) wireless transmission imposes huge
challenges on the design of efficient hardware architectures for iterative
receivers. A major challenge is soft-input soft-output (SISO) MIMO demapping,
often approached by sphere decoding (SD). In this paper, we introduce the - to
our best knowledge - first VLSI architecture for SISO SD applying a single
tree-search approach. Compared with a soft-output-only base architecture
similar to the one proposed by Studer et al. in IEEE J-SAC 2008, the
architectural modifications for soft input still allow a one-node-per-cycle
execution. For a 4x4 16-QAM system, the area increases by 57% and the operating
frequency degrades by 34% only.Comment: Accepted for IEEE Transactions on Circuits and Systems II Express
Briefs, May 2010. This draft from April 2010 will not be updated any more.
Please refer to IEEE Xplore for the final version. *) The final publication
will appear with the modified title "A Scalable VLSI Architecture for
Soft-Input Soft-Output Single Tree-Search Sphere Decoding
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