Soft-output Maximum Likelihood Research Articles

Low-complexity soft ML detection for generalized spatial modulation

Generalized Spatial Modulation (GSM) is a recent Multiple-Input Multiple-Output (MIMO) scheme, which achieves high spectral and energy efficiencies. Specifically, soft-output detectors have a key role in achieving the highest coding gain when an error-correcting code (ECC) is used. Nowadays, soft-output Maximum Likelihood (ML) detection in MIMO-GSM systems leads to a computational complexity that is unfeasible for real applications; however, it is important to develop low-complexity decoding algorithms that provide a reasonable computational simulation time in order to make a performance benchmark available in MIMO-GSM systems. This paper presents three algorithms that achieve ML performance. In the first algorithm, different strategies are implemented, such as a preprocessing sorting step in order to avoid an exhaustive search. In addition, clipping of the extrinsic log-likelihood ratios (LLRs) can be incorporating to this algorithm to give a lower cost version. The other two proposed algorithms can only be used with clipping and the results show a significant saving in computational cost. Furthermore clipping allows a wide-trade-off between performance and complexity by only adjusting the clipping parameter.

C-band PAM-4 signal transmission using soft-output MLSE and LDPC code.

We propose a DSP scheme with soft-output maximum likelihood sequence equalizer (sMLSE) and low-overhead (8.51%) low density parity check (LDPC) code for C-band PAM-4 transmission. In order to apply LDPC code in conjunction with MLSE, the conventional hard-output MLSE is modified to have a soft-output value by using the Max-log BCJR algorithm. The feasibility of this approach is experimentally investigated in a 56 Gb/s C-band PAM-4 system. In order to investigate the advantages of the proposed scheme, we compare the performance of the sMLSE-LDPC code to that of MLSE-RS code. Relatively, additional OSNR gain of 0.6 dB ~2.1 dB is achieved. The variation of the relative OSNR gain depends on the burst errors, which originate from the power fading effect. By using an interleaver that spreads burst errors in time, one can see that the relative OSNR gain is improved as 1.6 dB ~2.1 dB. Using the proposed scheme with the interleaver, one can see that the 30 km transmission of 56 Gb/s PAM-4 in the C-band was experimentally demonstrated.

Detection of GSM and GSSK Signals with Soft-Output Demodulators

A special case of conventional spatial modulation (SM) is demonstrated in space shift keying (SSK) modulation, where the amplitude and/or phase modulation symbols are eliminated from the transmission process so as to reduce system complexity. However, the spectral efficiencies of both schemes increase only logarithmically. Hence, large antenna arrays are required to achieve high spectral efficiencies. To reduce the transceiver overhead, while achieving improved spectral efficiencies in both SM and SSK, generalised SM (GSM) and generalised SSK (GSSK), respectively, were proposed. Typically, in coded channels, soft-output detection coupled with soft-input channel decoding yields significant signal-to-noise ratio (SNR) gain. Hence, in this paper, we propose soft-output maximum-likelihood (ML) detectors (SOMLDs) for the GSM and GSSK schemes, with an aim to further improve the error performance of the systems. Monte Carlo simulation results demonstrate that the error performance of the proposed SOMLD schemes closely match with that of their hard-decision ML detector counterparts in uncoded channels; while significant SNR gains are yielded in coded channels.

Maximum likelihood soft-output detection through Sphere Decoding combined with box optimization

This paper focuses on the improvement of known algorithms for maximum likelihood soft-output detection. These algorithms usually have large computational complexity, that can be reduced by using clipping. Taking two well-known soft-output maximum likelihood algorithms (Repeated Tree Search and Single Tree Search) as a starting point, a number of modifications (based mainly on box optimization techniques) are proposed to improve the efficiency of the search. As a result, two new algorithms are proposed for soft-output maximum likelihood detection. One of them is based on Repeated Tree Search (which can be applied with and without clipping). The other one is based on Single Tree Search, which can only be applied to the case with clipping. The proposed algorithms are compared with the Single Tree Search algorithm, and their efficiency is evaluated in standard detection problems (4×4 16-QAM and 4×4 64-QAM) with and without clipping. The results show that the efficiency of the proposed algorithms is similar to that of the Single Tree Search algorithm in the case 4×4 16-QAM; however, in the case 4×4 64-QAM, the new algorithms are far more efficient than the Single Tree Search algorithm.

Coherent transceiver operating at 61-Gbaud/s.

We use 85-Gs/s digital-to-analog convertor (DAC), 85Gs/s analog-to-digital convertor (ADC), commercial optoelectronic (OE) components with an overall electronic 3dB-bandwidth of less than 15GHz, and novel digital signal processing (DSP) algorithms implemented in CMOS to realize real time coherent transceiver operation at a record baud rate of 61-Gbaud/s. Novel DSP approaches for mitigating narrow filtering effect is critical to acquire data clock, and to improve modem performance. With transmitter pre-emphasis, novel timing recovery, and soft output maximum likelihood sequence estimation (MLSE), we are able to achieve error free operation of single carrier 200-Gbit/s polarization division multiplexed quadrature phase shift keying (PDM-QPSK) after forward error correction (FEC) at 15.2dB OSNR with pre-FEC error rate of 1.4E-2, and single carrier 400-Gbit/s PDM 16-ary quadrature amplitude modulation (16QAM) after FEC at 30.2dB OSNR with pre-FEC error rate of 9.5E-3. Error free transmission for 200-Gbit/s PDM-QPSK and 400-Gbit/s PDM-16QAM was achieved after 1200km propagation with 6dB link margin and 80km propagation respectively.

Soft‐output space‐time block coded spatial modulation

Space-time block coded spatial modulation (STBC-SM) is a recently proposed multiple-input–multiple-output transmission scheme, which combines spatial modulation (SM) and Alamouti's space-time block code (STBC) in such a manner so as to retain the primary advantages of SM and STBC, while avoiding their drawbacks, resulting in an improved system error performance. In this study, the authors propose a soft-output maximum-likelihood (ML) detector (SOMLD) and a soft-output low-complexity near-ML detector (SOLCD) for STBC-SM transmission. Monte-Carlo simulations demonstrate that the error performance of the proposed schemes are able to closely match that of the hard decision ML detector for uncoded channel conditions, while significant improvement in error performance is demonstrated for coded systems. Furthermore, compared with SOMLD, SOLCD imposes a significantly lower computational complexity, while achieving near-ML error performance.

A low complexity soft-output detection algorithm for 2×2 multiple-input multiple-output multiband-ofdm systems using dual carrier modulation

This paper presents a low complexity soft-output detection algorithm for 2×2 multiple-input multiple-output (MIMO) multiband-orthogonal frequency division multiplexing (MB-OFDM) systems using dual carrier modulation (DCM) or modified DCM (MDCM). By detecting each symbol pair of DCM or MDCM separately, the proposed detection algorithm reduces the complexity of the partial Euclidean distance (PED) calculation and the preprocessing complexity, which is the complexity of QR decomposition and channel ordering. This paper also proposes an efficient candidate list extension method for soft-output MIMO detection by using the calculated PEDs. Because the proposed algorithm has a low complexity and can also be implemented in a fully-pipelined hardware, the proposed algorithm is suitable for MB-OFDM systems requiring high speed hardware. The simulation results of applying the proposed algorithm to 2×2 MIMO MB-OFDM systems using DCM or MDCM show that the performance of the proposed algorithm has near soft-output maximum likelihood detection performance. The hardware complexity of the proposed algorithm is approximately 40% of that of the existing algorithm with similar performance.

효율적인 노드 삽입을 이용한 순서화된 병렬 트리-탐색 기반 저복잡도 연판정 다중 안테나 검출 알고리즘

This paper proposes an low-complexity soft-output multiple-input multiple-output (soft-MIMO) detection algorithm for achieving soft-output maximum-likelihood (soft-ML) performance under max-log approximation. The proposed algorithm is based on a parallel tree-search (PTS) applying a channel ordering by a sorted-QR decomposition (SQRD) with altered sort order. The empty-set problem that can occur in calculation of log-likelihood ratio (LLR) for each bit is solved by inserting additional nodes at each search level. Since only the closest node is inserted among nodes with opposite bit value to a selected node, the proposed node insertion scheme is very efficient in the perspective of computational complexity. The computational complexity of the proposed algorithm is approximately 37-74% of that of existing algorithms, and from simulation results for a system, the proposed algorithm shows a performance degradation of less than 0.1dB.

Soft-output ML detector for spatial modulation OFDM systems

The spatial modulation (SM) divides input data into antenna indexes and data symbols, and transmits data symbols via the specific antenna chosen by the antenna index. Soft decision technology for the SM system has not been developed, and there is room for improving the receive performance. In this paper, soft-output maximum likelihood (ML) detector for antenna index and data bit is derived to recover the desired signals by soft decision. Simulation results show that the conventional SM system with hard decision has a limitation in its performance as compared to SIMO (single-input multiple-output) system. On the other hand, the proposed SM with soft decision outperforms the SM with ML detector based on hard decision.

Modified SC-Type Turbo Detection Using SISO MLD for CCI Suppression in SDM OFDM Systems

In space division multiplexing with orthogonal frequency division multiplexing (SDM–OFDM) systems, since co-channel interference (CCI) degrades the demodulation performance, CCI suppression is essential. For CCI suppression, the turbo detector using the soft-input soft-output maximum likelihood detector (SISO–MLD) is proposed. Although SISO–MLD can deal with soft information, SISO–MLD updates only a priori information of code bits at each iteration. This prevents the performance to be improved. Meanwhile, a turbo detector with soft cancellation (SC) followed by minimum mean square error (MMSE) filter, in which the variance of the residual interference components as well as a priori information can be updated at each iteration, is well known. However, the performance of SC/MMSE detector is also limited because it is proposed to reduce the computational complexity at the cost of performance degradation. In this paper, we propose an SC-type turbo detector which uses SISO–MLD for SDM–OFDM systems. In our proposed detector, the soft cancellation unit of the SC-type turbo detector is modified to cope with the SISO–MLD. From the simulation results, the proposed SC/MLD provides a better BER performance than the turbo detector using SISO–MLD. Furthermore, the proposed SC/MLD can attain the bit error rate (BER) equivalent to that of the SC/MMSE detector with a smaller computational complexity.