Spatial modulation (Sm), renowned for its high energy efficiency, stands as a pivotal massive mImO transmission technique. Leveraging the parallel processing capability and superior error rate performance, the m-algor...
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Spatial modulation (Sm), renowned for its high energy efficiency, stands as a pivotal massive mImO transmission technique. Leveraging the parallel processing capability and superior error rate performance, the m-algorithm to maximum likelihood (mmL) algorithm has emerged as a competitive demodulation method for Sm systems. In mmL, judicious configuration of layer widths can effectively diminish complexity. Nevertheless, existing literature, to the best of our knowledge, relies on empirical settings for layer widths, lacking a formal optimization strategy. In this letter, we propose a layer width optimization algorithm based on mathematical analysis and monte Carlo simulations. Numerical results have demonstrated that the mmL algorithm coupled with our proposed layer width configuration method yields the symbol vector error rate (SVER) comparable to the state-of-the-art optimal demodulation, while achieving a noteworthy complexity reduction.
The well-known m-algorithm and the newer T-algorithm are two closely related reduced-complexity trellis-search algorithms that can be used for data sequence estimation in digital communication systems. VLSI implementa...
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The well-known m-algorithm and the newer T-algorithm are two closely related reduced-complexity trellis-search algorithms that can be used for data sequence estimation in digital communication systems. VLSI implementations of these algorithms are attractive due to the parallelism and simplicity of their operation. While a small number of VLSI structures have been proposed previously, this paper describes new sorting-based architectures that can be used to realize these algorithms. Specifically, schemes based on odd-even transposition, insertion, and weavesorting techniques are presented. Structures are evaluated on the basis of area, time, and power measures. Actual VLSI implementations have been used to verify timing models.
Continuous phase modulation (CPm) signals may be precoded by a convolutional code followed by a mapping rule. Better codes may, however, be obtained by a more general code formed by a finite state machine. We provide ...
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Continuous phase modulation (CPm) signals may be precoded by a convolutional code followed by a mapping rule. Better codes may, however, be obtained by a more general code formed by a finite state machine. We provide improved codes for one such finite state machine. A new description of codes and design rules are presented. Better results are demonstrated for the partial response CPm schemes and previous optimum results are matched for the full response case. Tests of an m-algorithm decoder achieve near maximum-likelihood performance with only a fraction of the complexity of the Viterbi algorithm.
In this paper, we propose three new sub-optimum, reduced complexity decoding algorithms for convolutional codes. The algorithms are based on the minimal trellis representation for the convolutional code and on the m-a...
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In this paper, we propose three new sub-optimum, reduced complexity decoding algorithms for convolutional codes. The algorithms are based on the minimal trellis representation for the convolutional code and on the m-algorithm. Since the minimal trellis has a periodically time-varying state profile, each algorithm has a different strategy to select the number of surviving states in each trellis depth. We analyse both the computational complexity, in terms of arithmetic operations, and the bit error rate performance of the proposed algorithms over the additive white Gaussian noise channel. Results demonstrate that considerable complexity reductions can be obtained at the cost of a small loss in the performance, as compared to the Viterbi decoder.
We propose a simplified noise-predictive partial response maximum likelihood (NPmL) system in conjunction with m-algorithm for dual-layered perpendicular magnetic recording channels. The complexity, which is increased...
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We propose a simplified noise-predictive partial response maximum likelihood (NPmL) system in conjunction with m-algorithm for dual-layered perpendicular magnetic recording channels. The complexity, which is increased by the construction of noise prediction filter, can be reduced through the m-algorithm. Despite the complexity of the proposed scheme (m = 4) is decreased to 1/4 than one of the full NP(12321)mL system, two Systems maintain almost the same bit-error rate and the detection performance of the noise-predictive maximum likelihood is better than that of the conventional PRmL.
This paper proposes an adaptive selection algorithm for the surviving symbol replica candidates (ASESS) based on the maximum reliability in maximum likelihood detection with QR decomposition and the m-algorithm (QRm-m...
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This paper proposes an adaptive selection algorithm for the surviving symbol replica candidates (ASESS) based on the maximum reliability in maximum likelihood detection with QR decomposition and the m-algorithm (QRm-mLD) for Orthogonal Frequency Division multiplexing (OFDm) multiple-input multiple-output (mImO) multiplexing. In the proposed algorithm, symbol replica candidates newly-added at each stage are ranked for each surviving symbol replica from the previous stage using multiple quadrant detection. Then, branch metrics are calculated only for the minimum number of symbol replica candidates with a high level of reliability using an iterative loop based on symbol ranking results. Computer simulation results show that the computational complexity of the QRm-mLD employing the proposed ASESS algorithm is reduced to approximately 1/4 and 1/1200 compared to that of the original QRm-mLD and that of the conventional mLD with squared Euclidian distance calculations for all symbol replica candidates, respectively, assuming the identical achievable average packet error rate (PER) performance in 4-by-4 mImO multiplexing with 16QAm data modulation. The results also show that 1-Gbps throughput is achieved at the average received signal energy per bit-to-noise power spectrum density ratio (E-b/N-0) per receiver antenna of approximately 9 dB using the ASESS algorithm in QRm-mLD associated with 16QAmmodulation and Turbo coding with the coding rate of 8/9 assuming a 100-mHz bandwidth for a 12-path Rayleigh fading channel (root mean square (r.m.s.) delay spread of 0.26 mu s and maximum Doppler frequency of 20 Hz).
The m-algorithm is a reduced complexity, breadth-first, trellis search alternative to the Viterbi algorithm. It is particularly useful when the number of trellis states is so large as to render Viterbi detection impra...
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The m-algorithm is a reduced complexity, breadth-first, trellis search alternative to the Viterbi algorithm. It is particularly useful when the number of trellis states is so large as to render Viterbi detection impractical. When dealing with complex or long target responses, values of m >= 16 may be required in order to approach mLD performance. Performing path selection for m >= 16 using previously reported methods can be computationally complex and prohibitive to practical hardware implementation. This paper details reduced complexity path selection networks for use with large values of m. A strategy for the construction of reduced complexity networks is presented and can be used to create networks for a variety of values of m and for other applications where m-algorithm detection can be employed. The use of these networks will allow for practical realisable hardware implementations of m-algorithm detectors for m >= 16.
This paper investigates joint design and optimization of both low density parity check （LDPC） codes and m-algorithm based detectors including iterative tree search （ITS） and soft-output m-algorithm （SOmA） in mul...
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This paper investigates joint design and optimization of both low density parity check （LDPC） codes and m-algorithm based detectors including iterative tree search （ITS） and soft-output m-algorithm （SOmA） in multiple-input multiple-output （mImO） systems via the tool of extrinsic information transfer （EXIT） charts. First, we present EXIT analysis for ITS and SOmA. We indicate that the extrinsic information transfer curves of ITS obtained by monte Carlo simulations based on output log-likelihood rations are not true EXIT curves, and the explanation for such a phenomenon is given, while for SOmA, the true EXIT curves can be computed, enabling the code design. Then, we propose a new design rule and method for LDPC code degree profile optimization in mImO systems. The algorithm can make the EXIT curves of the inner decoder and outer decoder match each other properly, and can easily attain the desired code with the target rate. Also, it can transform the optimization problem into a linear one, which is computationally simple. The significance of the proposed optimization approach is validated by the simulation results that the optimized codes performmuch better than standard non-optimized ones when used together with SOmA detector.
This paper presents a robust and efficient detection algorithm for mImO wireless systems. The proposed scheme employs a novel combination of bit-level signal representation, mmSE-preprocessing and m-algorithm. The pro...
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This paper presents a robust and efficient detection algorithm for mImO wireless systems. The proposed scheme employs a novel combination of bit-level signal representation, mmSE-preprocessing and m-algorithm. The proposed bit-level algorithm exploits the structure of the QAm constellation by separating each bit of the signal to reduce the associated complexity of the listing and metric updating steps. In the joint detection/decoding systems, the proposed scheme visits less number of nodes by exploiting the extrinsic information obtained by the decoder. Our scheme may be employed in the rank-deficient system. Simulation results demonstrate that the bit-level detector achieves almost the same performance as the existing m-algorithm and it achieves a more significant gain in terms of complexity reduction.
This paper presents a novel low-complexity multiple-input multiple-output (mImO) detection scheme using a distributed m-algorithm (Dm) to achieve high performance soft mImO detection. To reduce the searching complexit...
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ISBN:
(纸本)9781424442966
This paper presents a novel low-complexity multiple-input multiple-output (mImO) detection scheme using a distributed m-algorithm (Dm) to achieve high performance soft mImO detection. To reduce the searching complexity, we build a mImO trellis graph and split the searching operations among different nodes, where each node will apply the m-algorithm. Instead of keeping a global candidate list as the traditional detector does, this algorithm keeps multiple small candidate lists to generate soft information. Since the Dmalgorithm can achieve good BER performance with a small m, the sorting cost of the Dmalgorithm is lower than that of the conventional K-best mImO algorithm. The proposed algorithm is very suitable for high speed parallel processing.
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