Recursive Systematic Convolutional Research Articles

Implementation of Novel Block and Convolutional Encoding Circuit Using FS-GDI

A novel implementation of Block and Convolutional encoding circuits approach using Gate Input Diffusion-Full Swing (FS-GDI) and Complementary Metal Oxide Semiconductor (CMOS) logic styles has been presented. Performance analysis of the proposed encoding circuits has been performed using Cadence Virtuoso (CV) S/W package. The performance metrics of FS-GDI-based encoding circuits have been compared with traditional CMOS-based designs. The proposed encoding circuits involve Block Hamming (15, 11), Convolutional (2, 1, 3), and Recursive Systematic Convolutional (2, 1, 2) encoding circuits; these presented circuits are simulated and tested using a word length of 11 bits. The simulation experiments revealed that the proposed implemented circuits achieve delay time improving by 27.91% and 33.27% for Hamming (15, 11) and Convolutional (2, 1, 3) codes, respectively. The simple proposed RSC encoder performs better than the Convolutional (2, 1, 3) due to shorter constraint length and less H/W complexity. On the other hand, the Transistor Count-Hardware (TC-H/W) is enhanced by 50% for the Block and Convolutional encoding based on employing area-efficient FS-GDI-XOR gate. From the analysis of the results, the proposed designs achieve efficient power and delay optimization of Hamming and Convolutional encoding utilizing the FS-GDI logic style. Also, it is clear that the characteristics of the proposed encoding circuits are vital and effective in the digital signal processing circuits and encoding/decoding schemes implementation in low-power wireless networks.

Concatenated turbo polar-convolutional codes based on soft cancellation algorithm

This paper presents the Parallel and Serial Concatenated Turbo Polar-Convolutional Codes (CTPCCs) to improve the performance of polar codes in the finite code length regime. Both proposed concatenated codes use the Systematic Polar Code (SPC) and Recursive Systematic Convolutional (RSC) code as constituent codes. The iterative decoding algorithms of the proposed systems consist of a Soft Cancellation (SCAN) decoder with a single internal iteration for the SPC and SOVA or LogMap decoder for the RSC code. The simulation results show that the performance of the Parallel Concatenated Turbo Polar-Convolutional Code (PCTPCC) at low signal-to-noise ratios (SNRs) is better than that of the Serial Concatenated Turbo Polar-Convolutional Code (SCTPCC) and also better than the performance of other Turbo Polar Codes (TPCs). At BER=10−2, the proposed PCTPCC with SOVA and LogMap algorithms has about 0.3 dB and 0.25 dB performance gains over the SCTPCC models, respectively. In the high SNR regions, the performance of the SCTPCC with the LogMap algorithm significantly outperforms that of other models. At BER=10−6, the proposed SCTPCC models with SOVA and LogMap algorithms outperform the PCTPCC model by gains of 0.3 dB and 0.25 dB, respectively. The PCTPCC model with the SOVA decoder is superior to other models in terms of complexity.

SP-DSTS-MIMO Scheme-Aided H.266 for Reliable High Data Rate Mobile Video Communication

With the ever growth of Internet users, video applications, and massive data traffic across the network, there is a higher need for reliable bandwidth-efficient multimedia communication. Versatile Video Coding (VVC/H.266) is finalized in September 2020 providing significantly greater compression efficiency compared to Highest Efficient Video Coding (HEVC) while providing versatile effective use for Ultra-High Definition (HD) videos. This article analyzes the quality performance of convolutional codes, turbo codes and self-concatenated convolutional (SCC) codes based on performance metrics for reliable future video communication. The advent of turbo codes was a significant achievement ever in the era of wireless communication approaching nearly the Shannon limit. Turbo codes are operated by the deployment of an interleaver between two Recursive Systematic Convolutional (RSC) encoders in a parallel fashion. Constituent RSC encoders may be operating on the same or different architectures and code rates. The proposed work utilizes the latest source compression standards H.266 and H.265 encoded standards and Sphere Packing modulation aided differential Space Time Spreading (SP-DSTS) for video transmission in order to provide bandwidth-efficient wireless video communication. Moreover, simulation results show that turbo codes defeat convolutional codes with an averaged Eb/N0 gain of 1.5 dB while convolutional codes outperform compared to SCC codes with an Eb/N0 gain of 3.5 dB at Bit Error Rate (BER) of . The Peak Signal to Noise Ratio (PSNR) results of convolutional codes with the latest source coding standard of H.266 is plotted against convolutional codes with H.265 and it was concluded H.266 outperform with about 6 dB PSNR gain at Eb/N0 value of 4.5 dB.

Low-Power VLSI Implementation of Novel Hybrid Adaptive Variable-Rate and Recursive Systematic Convolutional Encoder for Resource Constrained Wireless Communication Systems

In the modern wireless communication system, digital technology has tremendous growth, and all the communication channels are slowly moving towards digital form. Wireless communication has to provide the reliable and efficient transfer of information between transmitter and receiver over a wireless channel. The channel coding technique is the best practical approach to delivering reliable communication for the end-users. Many conventional encoder and decoder units are used as error detection and correction codes in the digital communication system to overcome the multiple transient errors. The proposed convolutional encoder consists of both Recursive Systematic Convolutional (RSC) Encoder and Adaptive Variable-Rate Convolutional (AVRC) encoder. Adaptive Variable-Rate Convolutional encoder improves the bit error rate performance and is more suitable for a power-constrained wireless system to transfer the data. Recursive Systematic Convolutional encoder also reduces the bit error rate and improves the throughput by employing the trellis termination strategy. Here, AVRC encoder ultimately acquires the channel state information and feeds the data into a fixed rate convolutional encoder and rate adaptor followed by a buffer device. A hybrid encoder combines the AVRC encoder and RSC encoder output serially and parallel, producing the solid encoded data for the modulator in the communication system. A modified turbo code is also obtained by placing interleaver between the two encoder units and building the stronger code word for the system. Finally, the conventional encoder system is compared and analyzed with the proposed method regarding the number of LUT’s, gates, clock cycle, slices, area, power, bit error rate, and throughput.

Performance Analysis of Iteratively Decoded Convergent Source Mapping with Sphere Packing-Assisted Differential Space-Time Spreading Technique for Efficient Video Transmission

With the substantial growth in number of wireless devices, future communication demands overarching research to design high-throughput and efficient systems. We propose an intelligent Convergent Source Mapping (CSM) approach incorporating Differential Space-Time Spreading (DSTS) technique with Sphere Packing (SP) modulation. The crux of CSM process is assured convergence by attaining an infinitesimal Bit-Error Rate (BER). Data Partitioning (DP) H.264 video codec is deployed to gauge the performance of our intelligent and efficient system. For the purpose of efficient and higher data rates, we have incorporated compression efficient source encoding along with error resiliency and transmission robustness features. The proposed system follows the concept of iterations between the Soft-Bit Source-Decoder (SBSD) and Recursive Systematic Convolutional (RSC) decoder. Simulations of the DSTS-SP-assisted CSM system are presented for the correlated narrowband Rayleigh channel, using different CSM rates but constant overall bit-rate budget. The SP-assisted DSTS systems are mainly useful in decoding algorithms that operate without requiring Channel State Information (CSI). The effects of incorporating redundancy via different CSM schemes on the attainable performance and convergence of the proposed system are investigated using EXtrinsic Information Transfer (EXIT) charts. The effectiveness of the proposed system is demonstrated through IT++ based proof-of-concept simulations. The Peak Signal-to-Noise Ratio (PSNR) analysis shows that using Rate-2/6 CSM with minimum Hamming distance ( d H , min ) of 4 offers about 5 dB gain, compared to an identical overall system code rate but with Rate-2/3 CSM and d H , min of 2. Furthermore, for a consistent value of d H , min and overall rate, the Rate-2/3 CSM scheme beats the Rate-5/6 CSM by about 2 dB at the PSNR degradation point of 2 dB. Moreover, the proposed system with Rate-2/3 CSM scheme furnishes an E b / N 0 gain of 20 dB when compared with the uniform-rate benchmarker. Clearly, we can say that higher d H , min and lower CSM values are favourable for our proposed setup.

On the Performance of Self‐Concatenated Coding for Wireless Mobile Video Transmission Using DSTS‐SP‐Assisted Smart Antenna System

In the current age of advanced technologies, there is an escalating demand for reliable wireless systems, catering to the high data rates of mobile multimedia applications. This article presents a novel approach to the concept of Self‐Concatenated Convolutional Coding (SECCC) with Sphere Packing (SP) modulation via Differential Space‐Time Spreading‐ (DSTS‐) based smart antennas. The two transmitters provide transmit diversity which is capable of recuperating the signal from the effects of fading, even with a single receiving antenna. The proposed DSTS‐SP SECCC scheme is probed for the Rayleigh fading channel. The SECCC structure is developed using the Recursive Systematic Convolutional (RSC) code with the aid of an interleaver. Interleaving generates randomness in exchange for extrinsic information between the constituent decoders. Iterative decoding is invoked at the receiving side to enhance the output performance by attaining fruitful convergence. The convergence behaviour of the proposed system is investigated using EXtrinsic Information Transfer (EXIT) curves. The performance of the proposed system is ascertained with the H.264 standard video codec. The perceived video quality of DSTS‐SP SECCC is found to be significantly better than that of the DSTS‐SP RSC. To be more precise, the proposed DSTS‐SP SECCC system exhibits an Eb/N0 gain of 8 dB at the PSNR degradation point of 1 dB, relative to the equivalent rate DSTS‐SP RSC. Similarly, an Eb/N0 gain of 10 dB exists for the DSTS‐SP SECCC system at 1 dB degradation point when compared with the SECCC scheme dispensing with the DSTS‐SP approach.

LOW POWER CODER FOR WIRELESS SENSOR NETWORKS

An Energy efficiency technique is a important subject for Wireless Sensor Networks (WSNs), that have received extensive attention to reduce energy consumption and improve network lifetime. Most of the power in sensor networks is consumed by data transmission and reception. This power can be reduced by using suitable data compression technique which reduces transmitted data over wireless channels. In this article, the design of an energy efficient coder is proposed. When this algorithm is applied to recursive systematic convolutional (RSC) code, it reduces both computation complexity and decode error probability. Applying this RSC code to wireless sensor network ensures correct data reception and reduced energy consumption. To validate and evaluate our work, simulation is done in Xilinx software and Power is calculated using Xilinx xpower tool. The simulation result shows that the proposed algorithm performs better than existing one

On the Performance of Wireless Video Communication Using Iterative Joint Source Channel Decoding and Transmitter Diversity Gain Technique

In this research work, we have presented an iterative joint source channel decoding- (IJSCD-) based wireless video communication system. The anticipated transmission system is using the sphere packing (SP) modulation assisted differential space-time spreading (DSTS) multiple input-multiple output (MIMO) scheme. SP modulation-aided DSTS transmission mechanism results in achieving high diversity gain by keeping the maximum possible Euclidean distance between the modulated symbols. Furthermore, the proposed DSTS scheme results in a low-complexity MIMO scheme, due to nonemployment of any channel estimation mechanism. Various combinations of source bit coding- (SBC-) aided IJSCD error protection scheme has been used, while considering their identical overall bit rate budget. Artificial redundancy is incorporated in the source-coded stream for the proposed SBC scheme. The motive of adding artificial redundancy is to increase the iterative decoding performance. The performance of diverse SBC schemes is investigated for identical overall code rate. SBC schemes are employed with different combinations of inner recursive systematic convolutional (RSC) codes and outer SBC codes. Furthermore, the convergence behaviour of the employed error protection schemes is investigated using extrinsic information transfer (EXIT) charts. The results of experiments show that our proposed R a t e − 2 / 3 SBC-assisted error protection scheme with high redundancy incorporation and convergence capability gives better performance. The proposed R a t e − 2 / 3 SBC gives about 1.5 dB E b / N 0 gain at the PSNR degradation point of 1 dB as compared to R a t e − 6 / 7 SBC-assisted error protection scheme, while sustaining the overall bit rate budget. Furthermore, it is also concluded that the proposed R a t e − 2 / 3 SBC-assisted scheme results in E b / N 0 gain of 24 dB at the PSNR degradation point of 1 dB with reference to R a t e − 1 SBC benchmarker scheme.

Recurrent neural network based turbo decoding algorithms for different code rates

Application of deep learning to error control coding is gaining special attention and neural network architectures on decoding are approached to compare with conventional ones. Turbo codes conventionally use BCJR algorithm for decoding. In this paper, performances of neural Turbo decoder and deep learning-based Turbo decoder are examined. A category of sequential codes are utilized to construct the RSC (Recursive Systematic Convolutional) codes as basic elements for Turbo encoder. Sequential codes suit the requirement of memory element present in convolution codes, which act as components for Turbo encoder. Turbo decoders are constructed by two means; as neural Turbo decoder and deep learning Turbo decoder. Both structures are based on recurrent neural network (RNN) architectures. RNN architectures are preferred due to the presence of memory as a feature. BER performance of both is compared with that of a convolutional Viterbi decoder in awgn channel. Both the structures are studied for different input data-lengths and code rates.

A High Throughput Hardware Architecture for Parallel Recursive Systematic Convolutional Encoders

During the last years, recursive systematic convolutional (RSC) encoders have found application in modern telecommunication systems to reduce the bit error rate (BER). In view of the necessity of increasing the throughput of such applications, several approaches using hardware implementations of RSC encoders were explored. In this paper, we propose a hardware intellectual property (IP) for high throughput RSC encoders. The IP core exploits a methodology based on the ABCD matrices model which permits to increase the number of inputs bits processed in parallel. Through an analysis of the proposed network topology and by exploiting data relative to the implementation on Zynq 7000 xc7z010clg400-1 field programmable gate array (FPGA), an estimation of the dependency of the input data rate and of the source occupation on the parallelism degree is performed. Such analysis, together with the BER curves, provides a description of the principal merit parameters of a RSC encoder.

Forward Error Correction Using Turbo Codes for Multimedia Data

The swift growth in multimedia technology of wireless network has made it mandatory for the efficient transmission across erratic channel. The transmission of encoded video using error control techniques is grabbing a great attention, since it works over the recovery of the lost data and errors in the bit frames which occur as a result of congestion and physical channel fading. Turbo codes are attracting researchers because of their efficient performance. The Turbo code is made up of analogous concatenation of two Recursive Systematic Convolutional (RSC) coders parted by a non-uniform interleaver. For different code rate and information block lengths greater than 104, these codes are capable of achieving low Bit-error rates (BERs) at SNRs within 1dB of Shannon’s limit. Turbo codes will assist to employ Viterbi decoders. More the number of iterations, higher is the error correction capacity and hence Turbo codes act as an elucidation for obtaining large coding gains.

Efficient and low latency turbo encoder design using Verilog-Hdl

Low complexity turbo-like codes based totally on the simple trellis or simple graph shape consequences in encoding with low complexity. Out of this Convolution, encoder and turbo codes are widely used due to the splendid errors control performance. The most famous communications encoding set of rules, the iterative deciphering calls for an exponential expansion in hardware complexity to acquire expanded encode accuracy. This paper makes a usage of Log-Map based Iterative decoding technique and specialty in the conclusion of the turbo encoder. The rapid codes are designed with the help of Recursive Systematic Convolution and are separated thru interleave, which (thing used to rearrange the bit collection) plays an essential position within the encoding technique. This paper offers the design of the parallel connection of Recursive Systematic Convolution (RSC) encoders and interleave to restrict postpone, results to form a turbo Encoder. The turbo Encoder is designed by way of Verilog-HDL and Synthesized through Xilinx ISE

Performance Analysis of OFDM System Using Pilots, Coding Bounds and MAP Decoder for Next Generation Applications

In this paper, an integrated Orthogonal Frequency Division Multiplexing (OFDM) system is developed to improve Bit Error Rate (BER) performance of communication systems in order to meet the requirements of advanced communication systems like long term evaluation advanced (LTE –A). The proposed OFDM system consists of channel estimation using comb type pilot arrangement and convolution encoder with the best known Coding Bounds and Maximum A Posteriori (MAP) decoder. Using pilot symbols, the channel quality is estimated. The BER performance of OFDM system is improved using pilot carriers, channel estimation schemes and MAP decoder at the best known coding bounds. The system performance is analyzed with recursive systematic and non-systematic convolution codes, ML and MAP decoders. From the results, it is evident that the proposed OFDM system with channel estimation and MAP decoder at the best known coding bounds improves the system performance significantly.

Large-scale MIMO is capable of eliminating power-thirsty channel coding for wireless transmission of HEVC/H.265 video

A wireless video transmission architecture relying on the emerging large-scale multiple-input--multiple-output (LS-MIMO) technique is proposed. Upon using the most advanced High Efficiency Video Coding (HEVC) (also known as H.265), we demonstrate that the proposed architecture invoking the low-complexity linear zero-forcing (ZF) detector and dispensing with any channel coding is capable of significantly outperforming the conventional small-scale MIMO based architecture, even if the latter employs the high-complexity optimal maximum-likelihood (ML) detector and a rate-$1/3$ recursive systematic convolutional (RSC) channel codec. Specifically, compared to the conventional small-scale MIMO system, the effective system throughput of the proposed LS-MIMO based scheme is increased by a factor of up to three and the quality of reconstructed video quantified in terms of the peak signal-to-noise ratio (PSNR) is improved by about $22.5\, \text{dB}$ at a channel-SNR of $E_b/N_0 \approx 6\,\text{dB}$ for delay-tolerant video-file delivery applications, and about $20\,\text{dB}$ for lip-synchronized real-time interactive video applications. Alternatively, viewing the attainable improvement from a power-saving perspective, a channel-SNR gain as high as $\Delta_{E_b/N_0}\approx 5\,\text{dB}$ is observed at a PSNR of $36\, \text{dB}$ for the scenario of delay-tolerant video applications and again, an even higher gain is achieved in the real-time video application scenario. Therefore, we envisage that LS-MIMO aided wireless multimedia communications is capable of dispensing with power-thirsty channel codec altogether!

OM2DNC: Opportunistic Max2-Degree Network Coding for wireless data broadcasting

In wireless broadcasting systems, multiple retransmissions are commonly employed to guarantee the correct reception of each packet. The traditional hybrid automatic retransmission request protocol retransmits one packet per slot. Hence, a large amount of retransmissions is required to correctly receive all the packets, which leads to low spectrum efficiency. In this paper, we propose an Opportunistic Max2-Degree Network Coding (OM2DNC) based wireless broadcasting (WBC) protocol. Specifically, to reduce the overall number of retransmissions, lost packets of different user equipments (UEs) are combined by performing Max-Degree network coding (NC) at the access node. Then, NC combined packets are broadcasted by utilizing the Max-Degree based opportunistic retransmission protocol. At each UE, the lost packet can be recovered by using the proposed joint network recursive systematic convolution decoder. Theoretical analyses and simulation results show that the average number of transmissions performance of the proposed OM2DNC based WBC protocol outperforms that of the traditional NC based WBC protocols.

Adaptive-Truncated-HARQ-Aided Layered Video Streaming Relying on Interlayer FEC Coding

Interlayer forward error correction (IL-FEC) coding constitutes an effective unequal error protection (UEP) scheme conceived for transmitting layered video over wireless channels. In contrast to traditional UEP schemes, it operates by embedding extra information concerning the base layer (BL) into the enhancement layers (ELs) without requiring extra transmission resources. The received EL packets assist in the decoding of the BL to reduce the distortion of the reconstructed video. The optimum scheduling of the IL-FEC coded layered video streaming in a truncated hybrid automatic repeat request (THARQ)-aided system is an open problem. Hence, in this paper, we conceive an adaptive THARQ (ATHARQ) algorithm for finding the most appropriate scheduling of the IL-FEC coded layered video packets for the sake of minimizing the video distortion under the constraint of a given total number of transmission time slots (TSs). Furthermore, we develop a method of online coding-rate optimization algorithm for our IL-ATHARQ transmission scheme to find the best FEC code rate distribution among the video layers that results in the lowest possible video distortion. When using a recursive systematic convolutional (RSC) code, our simulation results show that the proposed rate-optimized (RO) IL-ATHARQ system outperforms the traditional THARQ transmission scheme by about 5.3 dB of $E_{b}/N_{0}$ at a peak signal-to-noise ratio (PSNR) of 38.5 dB. Viewing the improvements in terms of the video quality, 2.5 dB of PSNR improvement is attained at an $E_{b}/N_{0}$ of 15 dB.

Capacity-Approaching TQC-LDPC Convolutional Codes Enabling Power-Efficient Decoders

In this paper, we develop a new capacity-approaching code, namely, parallel-concatenated (PC)-Low Density Parity Check (LDPC) convolutional code that is based on the parallel concatenation of trellis-based quasi-cyclic LDPC (TQC-LDPC) convolutional codes. The proposed PC-LDPC convolutional code can be derived from any QC-LDPC block code by introducing the trellis-based convolutional dependency to the code. The capacity-approaching PC-LDPC convolutional codes are encoded through parallel concatenated trellis-based QC recursive systematic convolutional (RSC) encoder (namely, QC-RSC encoder) that is also proposed in this paper. The proposed PC-LDPC convolutional code and the associated encoder retain a fine input granularity on the order of the lifting factor of the underlying block code. We also describe the corresponding trellis-based QC maximum a posteriori probability (namely, QC-MAP) decoder that efficiently decodes the PC-LDPC convolutional code. Performance and hardware implementation results show that the PC-LDPC convolutional codes with the QC-MAP decoder have two times lower complexity for a given bit-error-rate (BER), signal-to-noise ratio, and data rate, than conventional QC-LDPC block codes and LDPC convolutional codes. Moreover, the PC-LDPC convolutional code with the QC-MAP decoder outperforms the conventional QC-LDPC block codes by more than 0.5 dB for a given BER, complexity, and data rate and approaches Shannon capacity limit with a gap smaller than 1.25 dB. This low decoding complexity and the fine granularity make it feasible to efficiently implement the proposed capacity-approaching PC-LDPC convolutional code and the associated trellis-based QC-MAP decoder in next generation ultra-high data rate mobile systems.

Hierarchical Colour-Shift-Keying Aided Layered Video Streaming for the Visible Light Downlink

Colour-shift keying (CSK) constitutes an important modulation scheme conceived for the visible light communications (VLC). The signal constellation of CSK relies on three different-color light sources invoked for information transmission. The CSK constellation has been optimized for minimizing the bit error rate, but no effort has been invested in investigating the feasibility of CSK aided unequal error protection (UEP) schemes conceived for video sources. Hence, in this treatise, we conceive a hierarchical CSK (HCSK) modulation scheme based on the traditional CSK, which is capable of generating interdependent layers of signals having different error probability, which can be readily reconfigured by changing its parameters. Furthermore, we conceived an HCSK design example for transmitting scalable video sources with the aid of a recursive systematic convolutional (RSC) code. An optimization method is conceived for enhancing the UEP and for improving the quality of the received video. Our simulation results show that the proposed optimized-UEP 16-HCSK-RSC system outperforms the traditional equal error protection scheme by $\sim 1.7$ dB of optical SNR at a peak signal-to-noise ratio of 37 dB, while optical SNR savings of up to 6.5 dB are attained at a lower PSNR of 36 dB.

Interleaving Gains for Receive Diversity Schemes of Distributed Turbo Codes in Wireless Half–Duplex Relay Channels

This paper proposes the interleaving gain in two different distributed turbo-coding schemes: Distributed Turbo Codes (DTC) and Distributed Multiple Turbo Codes (DMTC) for half-duplex relay system as an extension of our previous work on turbo coding interleaver design for direct communication channel. For these schemes with half-duplex constraint, the source node transmits its infor- mation with the parity bit sequence(s) to both the relay and the destination nodes during the first phase. The relay received the data from the source and process it by using decode and forward protocol. For the second transmission period, the decoded systematic data at relay is interleaved and re-encoded by a Recursive Systematic Convolutional (RSC) encoder and forwarded to the destination. At desti- nation node, signals received from the source and relay nodes are processed by using turbo log-MAP iterative decoding for retrieving the original information bits. We demonstrate via simulations that the interleaving gain has a large effect with DTC scheme when we use only one RSC encoder at both the source and relay with best performance when using Modified Matched S-Random (MMSR) inter- leaver. Furthermore, by designing a Chaotic Pseudo Ran- dom Interleaver (CPRI) as an outer interleaver at the source node instead of classical interleavers, our scheme can add more secure channel conditions.

Distributed State Estimation Using RSC Coded Smart Grid Communications

Recently, the renewable distributed energy resources (DERs) have become more and more popular due to carbon-free energy sources and environment-friendly electricity generation. Unfortunately, these power generation patterns are mostly intermittent in nature and distributed over the electrical grid, which creates challenging problems in the reliability of the smart grid. Thus, the smart grid has a strong requisite for an efficient communication infrastructure to facilitate estimating the DER states. In contrast to the traditional methods of centralized state estimation (SE), we propose a distributed approach to microgrid SE based on the concatenated coding structure. In this framework, the DER state is treated as a dynamic outer code, and the recursive systematic convolutional (RSC) code is seen as a concatenated inner code for protection and redundancy in the system states. Furthermore, in order to properly monitor the intermittent energy source from any place, this paper proposes a distributed SE method. Particularly, the outputs of the local SE are treated as measurements, which are fed into the master fusion station. At the end, the global SE can be obtained by combining local SEs with corresponding weighting factors. The weighting factors can be calculated by inspiring the covariance intersection method. The simulation results show that the proposed method is able to estimate the system state properly.