In recent years, physical layer security (PLS), which is based on information theory and whose strength does not depend on the eavesdropper's computing capability, has attracted much attention. We have proposed a chaos modulation method as one PLS method that offers channel coding gain. One alternative is based on polar codes. They are robust error-correcting codes, have a nested structure in the encoder, and the application of this mechanism to PLS encryption (PLS-polar) has been actively studied. However, most conventional studies assume the application of conventional linear modulation such as BPSK, do not use encryption modulation, and the channel coding gain in the modulation is not achieved. In this paper, we propose a PLS-polar method that can realize high-quality transmission and encryption of a modulated signal by applying chaos modulation to a polar-coding system. Numerical results show that the proposed method improves the performance compared to the conventional PLS-polar method by 0.7dB at a block error rate of 10-5. In addition, we show that the proposed method is superior to conventional chaos modulation concatenated with low-density parity-check codes, indicating that the polar code is more suitable for chaos modulation. Finally, it is demonstrated that the proposed method is secure in terms of information theoretical and computational security.

In a multiple-input multiple-output (MIMO) system, maximum likelihood detection (MLD) is the best demodulation scheme if no a priori information is available. However, the complexity of MLD increases exponentially with the number of signal streams. Therefore, various demodulation schemes with less complexity have been proposed and some of those schemes show performance close to that of MLD. One kind of those schemes uses a Gibbs sampling (GS) algorithm. GS MIMO detection that combines feedback from turbo decoding has been proposed. In this scheme, the accuracy of GS MIMO detection is improved by feeding back loglikelihood ratios (LLRs) from a turbo decoder. In this paper, GS MIMO detection using only feedback LLRs from a turbo decoder is proposed. Through extrinsic information transfer (EXIT) chart analysis, it is shown that the EXIT curves with and without metrics calculated from received signals overlap as the feedback LLR values increase. Therefore, the proposed scheme calculates the metrics from received signals only for the first GS MIMO detection and the selection probabilities of GS MIMO detection in the following iterations are calculated based only on the LLRs from turbo decoders. Numerical results obtained through computer simulation show that the performance of proposed GS turbo MIMO detection is worse than that of conventional GS turbo MIMO detection when the number of GS iterations is small. However the performance improves as the number of GS iterations increases. When the number of GS iterations is 30 or more, the bit error rate (BER) performance of the proposed scheme is equivalent to that of the conventional scheme. Therefore, the proposed scheme can reduce the computational complexity of selection probability calculation in GS turbo MIMO detection.

For high transmission efficiency, good modulation schemes are expected. This paper focuses on the enhancement of the modulation scheme of free space optical turbo coded system. A free space optical turbo coded system using a new signaling scheme called hybrid PPM-OOK signaling (HPOS) is proposed and investigated. The theoretical formula of the bit error rate of the uncoded HPOS system is derived. The effective information rate performances (i.e. channel capacity) of the proposed HPOS turbo coded system are evaluated through computer simulation in free space optical channel, with weak, moderate, strong scintillation. The performance of the proposed HPOS turbo coded system is compared with those of the conventional OOK (On-Off Keying) turbo coded system and BPPM (Binary Pulse Position Modulation) turbo coded system. As results, the proposed HPOS turbo coded system shows the same tolerance capability to background noise and atmospheric turbulence as the conventional BPPM turbo coded system, and it has 1.5 times larger capacity.

This paper proposed an iterative soft interference canceller (IC) referred to as turbo equalizer for the self-coherent detection, and extrinsic information transfer (EXIT) chart based irregular low density parity check (LDPC) code optimization for the turbo equalizer in optical fiber short-reach transmissions. The self-coherent detection system is capable of linear demodulation by a single photodiode receiver. However, the self-coherent detection suffers from the interference induced by signal-signal beat components, and the suppression of the interference is a vital goal of self-coherent detection. For improving the error-free signal detection performance of the self-coherent detection, we proposed an iterative soft IC with the aid of forward error correction (FEC) decoder. Furthermore, typical FEC code is no longer appropriate for the iterative detection of the turbo equalizer. Therefore, we designed an appropriate LDPC code by using EXIT chart aided code design. The validity of the proposed turbo equalizer with the appropriate LDPC is confirmed by computer simulations.

This paper proposes a sequentially iterative equalizer based on Kalman filtering and smoothing (SIEKFS) for multiple-input multiple-output (MIMO) systems under frequency selective fading channels. In the proposed SIEKFS, an iteration consists of sequentially executed subiterations, and each subiteration performs equalization and detection procedures of the symbols transmitted from a specific transmit antenna. During this subiteration, all available observations for the transmission block are utilized in the equalization procedures. Furthermore, the entire soft estimate of the desired symbols to be detected does not participate in the equalization procedures of the desired symbols, i.e., the proposed SIEKFS performs input-by-input equalization procedures for a priori information nulling. Therefore, compared with the original iterative equalizer based on Kalman filtering and smoothing, which performs symbol-by-symbol equalization procedures, the proposed SIEKFS can also perform iterative equalization based on the Kalman framework and turbo principle, with a significant reduction in computation complexity. Simulation results verify that the proposed SIEKFS achieves suboptimum error performance as the size of the antenna configuration and the number of iterations increase.

This paper presents an approximated log-likelihood ratio calculation scheme with bit shifts and summations. Our previous work yielded a metric calculation scheme that replaces multiplications with bit shifts and summations in the selection of candidate signal points for joint maximum likelihood detection (MLD). Log-likelihood ratio calculation for turbo decoding generally uses multiplications and by replacing them with bit shifts and summations it is possible to reduce the numbers of logic operations under specific transmission parameters. In this paper, an approximated log-likelihood ratio calculation scheme that substitutes bit shifts and summations for multiplications is proposed. In the proposed scheme, additions are used only for higher-order bits. Numerical results obtained through computer simulation show that this scheme can eliminate multiplications in turbo decoding at the cost of just 0.2dB performance degradation at a BER of 10-4.

In this study, an anonymization infrastructure for the secondary use of data is proposed. The proposed infrastructure can publish data that includes privacy information while preserving the privacy by using anonymization techniques. The infrastructure considers a situation where ill-motivated users redistribute the data without authorization. Therefore, we propose a watermarking method for anonymized data to solve this problem. The proposed method is implemented, and the proposed method's tolerance against attacks is evaluated.

The sub-blocking algorithm has been known as a core component in implementing a turbo decoder using a Graphic Processing Unit (GPU) to use as many cores in the GPU as possible for parallel processing. However, even though the sub-blocking algorithm allows a large number of threads in a given GPU to be adopted for processing a large number of sub-blocks in parallel, each thread must access the global memory with strided addresses, which results in uncoalesced memory access. Because uncoalesced memory access causes a lot of unnecessary memory transactions, the memory bandwidth efficiency drops significantly, possibly as low as 1/8 in the case of an Long Term Evolution (LTE) turbo decoder, depending upon the compute capability of a GPU. In this paper, we present a novel method for converting uncoalesced memory access into coalesced access in a way that completely recovers the memory bandwidth efficiency to 100% without additional overhead. Our experimental tests, performed with NVIDIA's Geforce GTX 780 Ti GPU, show that the proposed method can enhance the throughput by nearly 30% compared with a conventional turbo decoder that suffers from uncoalesced memory access. Throughput provided by the proposed method has been observed to be 51.4Mbps when the number of iterations and that of sub-blocks are set to 6 and 32, respectively, in our experimental tests, which far exceeds the performance of previous works implemented the Max-Log-MAP algorithm.

Physical layer security is effective in wireless communications because it makes a transmission secure from the beginning of protocols. We have proposed a chaos multiple-input multiple-output (C-MIMO) transmission scheme that achieves both physical layer security and channel coding gain using chaos signals. C-MIMO is a type of encryption modulation and it obtains the coding gain in conjunction with encryption without a decrease in the transmission efficiency. Thus, the error rate performance is improved in C-MIMO. However, decoding complexity increases exponentially with code length because of the use of maximum likelihood sequence estimation (MLSE), which restricts the code length of C-MIMO and thus the channel coding gain. Therefore, in this paper, we consider outer channel code concatenation instead of code length expansion for C-MIMO, and propose an iterative turbo decoding scheme for performance improvement by introducing a log-likelihood ratio (LLR) into C-MIMO and by utilizing turbo principle. The improved performances of the proposed scheme, compared to the conventional scheme when the outer channel codes are convolutional code and low-density parity check (LDPC) code, are shown by computer simulations.

Open-loop (OL) transmit diversity is more subject to the influence of channel estimation error than closed-loop (CL) transmit diversity, although it has the merit of providing better performance in fast Doppler frequency environments because it doesn't require a feedback signal. This paper proposes an OL transmit diversity scheme combined with intra-subframe frequency hopping (FH) and iterative decision-feedback channel estimation (DFCE) in a shared channel for discrete Fourier transform (DFT)-precoded orthogonal frequency division multiple access (OFDMA). We apply intra-subframe FH to OL transmit diversity to mitigate the reduction in the diversity gain under high fading correlation conditions among antennas and iterative DFCE to improve the channel estimation accuracy. Computer simulation results show that the required average received signal-to-noise power ratio at the average block error rate (BLER) of 10-2 of the space-time block code (STBC) with intra-subframe FH is reduced to within approximately 0.8dB compared to codebook-based CL transmit diversity when using iterative DFCE at the maximum Doppler frequency of fD =5.55Hz. Moreover, it is shown that STBC with intra-subframe FH and iterative DFCE achieves much better BLER performance compared to CL transmit diversity when fD is higher than approximately 30Hz since the tracking ability of the latter degrades due to the fast fading variation in its feedback loop.

This paper presents comprehensive comparisons on the block error rate (BLER) performance of rate-one open-loop (OL) transmit diversity schemes with four antennas for discrete Fourier transform (DFT)-precoded Orthogonal Frequency Division Multiple Access (OFDMA). One candidate scheme employs a quasi-orthogonal (QO) - space-time block code (STBC) in which four-branch minimum mean-square error (MMSE) combining is achieved at the cost of residual inter-code interference (ICI). Another candidate employs a combination of the STBC and selection transmit diversity called time switched transmit diversity (TSTD) (or frequency switched transmit diversity (FSTD)). We apply a turbo frequency domain equalizer (FDE) associated with iterative decision-feedback channel estimation (DFCE) using soft-symbol estimation to reduce channel estimation (CE) error. The turbo FDE includes an ICI canceller to reduce the influence of the residual ICI for the QO-STBC. Based on link-level simulation results, we show that a combination of the STBC and TSTD (or FSTD) is suitable as a four-antenna OL transmit diversity scheme for DFT-precoded OFDMA using the turbo FDE and iterative DFCE.

In this paper, we investigate iterative detection and decoding, a.k.a. turbo detection, for multiple-input multiple-output (MIMO) transmission. Specifically, we consider using a low complexity soft-in/soft-out MIMO detector based on belief propagation over a pair-wise graph that accepts a priori information feedback from a channel decoder. Simulation results confirm that considerable performance improvement can be obtained with only a few detection-and-decoding iterations if convolutional channel coding is used. A brief estimate is given of the overall complexity of turbo detectors, to verify the key argument that the performance of a maximum a posteriori (MAP) detector (without turbo iteration) can be achieved, at much lower computation cost, by using the low complexity soft-in/soft-out MIMO detector under consideration.

Turbo mode, which accelerates many applications without major change of existing systems, is widely used in commercial processors. Since time duration or powerfulness of turbo mode depends on peak temperature of a processor chip, reducing the peak temperature can reinforce turbo mode. This paper presents that adding small amount of hardware allows microprocessors to reduce the peak temperature drastically and then to reinforce turbo mode successfully. Our approach is to find out a few small units that become heat sources in a processor and to appropriately duplicate them for reduction of their power density. By duplicating the limited units and using the copies evenly, the processor can show significant performance improvement while achieving area-efficiency. The experimental result shows that the proposed method achieves up to 14.5% of performance improvement in exchange for 2.8% of area increase.

In this paper, we propose a fully parallel Turbo decoder for Software-Defined Radio (SDR) on the Graphics Processing Unit (GPU) platform. Soft Output Viterbi algorithm (SOVA) is chosen for its low complexity and high throughput. The parallelism of SOVA is fully analyzed and the whole codeword is divided into multiple sub-codewords, where the turbo-pass decoding procedures are performed in parallel by independent sub-decoders. In each sub-decoder, an efficient initialization method is exploited to assure the bit error ratio (BER) performance. The sub-decoders are mapped to numerous blocks on the GPU. Several optimization methods are employed to enhance the throughput, such as the memory optimization, codeword packing scheme, and asynchronous data transfer. The experiment shows that our decoder has BER performance close to Max-Log-MAP and the peak throughput is 127.84Mbps, which is about two orders of magnitude faster than that of central processing unit (CPU) implementation, which is comparable to application-specific integrated circuit (ASIC) solutions. The presented decoder can achieve higher throughput than that of the existing fastest GPU-based implementation.

This paper studies the performance of code-aided (CA) soft-information based carrier phase recovery, which iteratively exploits the extrinsic information from channel decoder to improve the accuracy of phase synchronization. To tackle the problem of strong coupling between phase recovery and decoding, a semi-analytical model is proposed to express the distribution of extrinsic information as a function of phase offset. Piecewise approximation of the hyperbolic tangent function is employed to linearize the expression of soft symbol decision. Building on this model, open-loop characteristic and closed-loop performance of CA iterative soft decision-directed (ISDD) carrier phase synchronizer are derived in closed-form. Monte Carlo simulation results corroborate that the proposed expressions are able to characterize the performance of CA ISDD carrier phase recovery for systems with different channel codes.

Turbo equalization is an iterative equalization and decoding technique that can achieve impressive performance gains for communication systems. In this letter, we investigate the turbo equalization method for the decoding of the Davey-MacKay (DM) construction over the IDS-AWGN channels, which indicates a cascaded insertion, deletion, substitution (IDS) channel and an additive white Gaussian noise (AWGN) channel. The inner decoder for the DM construction can be seen as an maximum a-posteriori (MAP) detector. It receives the beliefs generated by the outer LDPC decoder when turbo equalization is used. Two decoding schemes with different kinds of inner decoders, namely hard-input inner decoder and soft-input inner decoder, are investigated. Simulation results show that significant performance gains are obtained for both decoders with respect to the insertion/deletion probability at different SNR values.

A highly parallel turbo decoder for 3GPP LTE/LTE-Advanced systems is presented. It consists of 32 radix-4 soft-in/soft-out (SISO) decoders. Each SISO decoder is based on the proposed full-parallel sliding window (SW) schedule. Implemented in a 0.13 µm CMOS technology, the proposed design occupies 12.96 mm2 and achieves 1.5 Gb/s while decoding size-6144 blocks with 5.5 iterations. Compared with conventional SW schedule, the throughput is improved by 30–76% with 19.2% area overhead and negligible energy overhead.

A stopping criterion is an indispensable function to reduce unnecessary power consumption and decoding delay in turbo decoding. Until now, a common design philosophy in previous works has involved using the entire block of information from the MAP decoder and its input/output information to calculate the stopping index. It is an intuitive method but suffers from heavy memory requirements and high calculation complexity. In this paper, a low-complexity stopping criterion is proposed that avoids the aforementioned disadvantages. A general abstraction model is utilized to analyze the design bottleneck of stopping criteria. Instead of using an entire block of information, a compact representation derived from the internal information of the MAP decoder at a single time instant is used as a low-complexity stopping index. Theoretical explanation is provided to justify the feasibility of the proposed criterion. Simulation results show that the proposed criterion can reduce the complexity of stopping criterion dramatically while continuing to achieve the same level of performance as previous works.

Physical-layer network coding with binary turbo coding in a two-way relay channel is considered. A two-user turbo decoding scheme is proposed with a simplified sum trellis. For two-user iterative decoding at a relay, the component decoder with its simplified sum trellis decodes the superimposed signal to the arithmetic sum of two users' messages. The simplified sum trellis is obtained by removing one of the states in a pair of mutual symmetrical states from a sum trellis. This removal reduces the decoding complexity to half of that with the sum trellis, and does not degrade decoding performance over AWGN channel since two output sequences from the pair of mutual symmetrical states are the same.

This paper proposes a spectrum-overlapped resource management (SORM) technique where each user equipment (UE) can ideally obtain the frequency selection diversity gain under multi-user environments. In the SORM technique for cellular systems, under assumption of adopting a soft canceller with minimum mean square error (SC/MMSE) turbo equalizer, an evolved node B (eNB) accepts overlapped frequency resource allocation. As a result, each UE can use the frequency bins having the highest channel gain. However, the SORM becomes non-orthogonal access when the frequency bins having high channel gain for UEs are partially identical. In this case, the inter-user interference (IUI) caused by overlapping spectra among UEs is eventually canceled out by using the SC/MMSE turbo equalizer. Therefore, SORM can achieve better performance than orthogonal access e.g. FDMA when the IUI is completely canceled. This paper demonstrates that SORM has the potential to improve transmission performance, by extrinsic information transfer (EXIT) analysis. Moreover, this paper evaluates the block error rate (BLER) performance of the SORM and the FDMA. Consequently, this paper shows that the SORM outperforms the FDMA.