Low Complexity Minimum Mean Square Error Channel Estimation for Adaptive Coding and Modulation Systems

Performance of the Adaptive Coding and Modulation(ACM) strongly depends on the retrieved Channel State Information(CSI),which can be obtained using the channel estimation techniques relying on pilot symbol transmission.Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little.In this paper,we investigate the performance of CSI prediction using the Minimum Mean Square Error(MMSE)channel estimator for an ACM system.To solve the two problems of MMSE:high computational operations and oversimplified assumption,we then propose the Low-Complexity schemes(LC-MMSE and Recursion LC-MMSE(R-LC-MMSE)).Computational complexity and Mean Square Error(MSE) are presented to evaluate the efficiency of the proposed algorithm.Both analysis and numerical results show that LC-MMSE performs close to the wellknown MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.

Improved Adaptive Random Convolutional Network Coding Algorithm

To address the issue of field size in random network coding, we propose an Improved Adaptive Random Convolutional Network Coding (IARCNC) algorithm to considerably reduce the amount of occupied memory. The operation of IARCNC is similar to that of Adaptive Random Convolutional Network Coding (ARCNC), with the coefficients of local encoding kernels chosen uniformly at random over a small finite field. The difference is that the length of the local encoding kernels at the nodes used by IARCNC is constrained by the depth; meanwhile, increases until all the related sink nodes can be decoded. This restriction can make the code length distribution more reasonable. Therefore, IARCNC retains the advantages of ARCNC, such as a small decoding delay and partial adaptation to an unknown topology without an early estimation of the field size. In addition, it has its own advantage, that is, a higher reduction in memory use. The simulation and the example show the effectiveness of the proposed algorithm.

LSTM-Based Adaptive Modulation and Coding for Satellite-to-Ground Communications

Satellite communication develops rapidly due to its global coverage and is unrestricted to the ground environment. However, compared with the traditional ground TCP/IP network, a satellite-to-ground link has a more extensive round trip time(RTT) and a higher packet loss rate,which takes more time in error recovery and wastes precious channel resources. Forward error correction(FEC) is a coding method that can alleviate bit error and packet loss, but how to achieve high throughput in the dynamic network environment is still a significant challenge. Inspired by the deep learning technique, this paper proposes a signal-to-noise ratio(SNR) based adaptive coding modulation method. This method can maximize channel utilization while ensuring communication quality and is suitable for satellite-to-ground communication scenarios where the channel state changes rapidly. We predict the SNR using the long short-term memory(LSTM) network that considers the past channel status and real-time global weather. Finally, we use the optimal matching rate(OMR) to evaluate the pros and cons of each method quantitatively. Extensive simulation results demonstrate that our proposed LSTM-based method outperforms the state-of-the-art prediction algorithms significantly in mean absolute error(MAE). Moreover, it leads to the least spectrum waste.

PERFORMANCES OF ADAPTIVE MODULATION AND CODING IN SATELLITE MOBILE CHANNEL

Given that satellite mobile channel is a time-varying channel,Adaptive Modulation and Coding(AMC) was proposed to provide robust and spectrally efficient transmission over satellite mobile channel.Three different kinds of channel environment were considered in this paper:the urban area,the rural area,and the open space.Four combinations of modulation and coding were designed to meet reliable communication on time-varying channel,and spectral efficiency and system throughput of these three kinds of channel environment were simulated.Based on the simulation results,this paper analysed the results and compared the performances of AMC with non-AMC system in these three kinds of channel environment.At last,we come to the conclusions:a system with AMC can achieve higher spectral efficiency and better system throughput;and the spectral efficiency and system throughput of AMC system will be higher on better satellite mobile channel.

Error Resilient Video Communication Based on Picture Level Adaptive Frame / Field Coding

Packet loss protection method based on picture level adaptive frame /field coding (PAFF)was presented. Firstly,the end-to-end rate-distortion analysis for PAFF on the current frame was performed. Secondly,in order to evaluate the severity of error propagation in the following frames,the error propagation intensity and human visual quality sensitivity of different areas were taken into consideration. It was followed by the quantification of relative importance. Finally,the proper coding mode was chosen utilizing an unequal comparison procedure. The simulation results show that the proposed method can improve peak signal-to-noise ratio (PSNR) up to 0. 9 dB and 1. 6 dB comparing with the field only and the dispersed flexible macro-block ordering (FMO)only methods respectively.

Adaptive Modulation and Coding Based on Fuzzy Logic Cognitive Engine

Adaptive modulation and coding( AMC) which depends on channel state information( CSI) can make the modulation and coding scheme( MCS) for the sender changed, and make the spectrum efficiency enhanced. The traditional method of AMC establishes a lookup table of MCSs at first,and then the sender chooses the proper MCS according to the CSI from feedback channel. However,this method is not suitable for frequency selective and fast fading channel. Thus, a method based on fuzzy logic cognitive engine is proposed in this paper. The type of channel is recognized by the fuzzy logic cognitive engine,then the MCSs are modified to suit for the channel type. The simulation results show that the proposed method is more suitable for frequency selective and fast fading channel. And it is more reliability under the condition of meeting the bit error rate( BER).

Feedback Stabilization over Wireless Network Using Adaptive Coded Modulation

In this paper,we apply adaptive coded modulation (ACM) schemes to a wireless networked control system (WNCS) to improve the energy efficiency and increase the data rate over a fading channel.To capture the characteristics of varying rate, interference,and routing in wireless transmission channels,the concepts of equivalent delay (ED) and networked condition index (NCI) are introduced.Also,the analytic lower and upper bounds of EDs are obtained.Furthermore,we model the WNCS as a multicontroller switched system (MSS) under consideration of EDs and loss index in the wireless transmission.Sufficient stability condition of the closed-loop WNCS and corresponding dynamic state feedback controllers are derived in terms of linear matrix inequality (LMI). Numerical results show the validity and advantage of our proposed control strategies.

Entanglement fidelity of channel adaptive quantum codes

We study the performances of quantum channel adaptive [4,1] code transmitting in a joint amplitude damping and dephasing channel, the [6,2] code transmitting in an amplitude damping channel by combining the encoding, noise process, and decoding as one effective channel. We explicitly obtain the entanglement fidelities. The recovery operators of the [6,2] code are given. The performance is nearly optimal compared with that of the optimal method of semidefinite programming.

A Joint Rate Control and AMC Algorithm for Adaptive Transmission Systems

The traditional communication system is effectively designed for the worst-case channel state and it can not use the spectral efficiently over the time-varying multipath channel. In order to improve the spectral efficiency and ensure robust and spectrally-efficient transmission over the time-varying multipath channel,a joint rate control and adaptive modulation and coding ( AMC) algorithm for adaptive transmission systems is proposed in this paper. Firstly,the proposed algorithm can formulate a modulation and coding scheme ( MCS) switching table according to the offline simulation results and the target bit error rate ( BER) . Then,the optimal MCS is selected in MCS switching table according to the channel state information ( CSI) and then passes to the transmitter and receiver to implement. So the adaptive system which always uses the optimal MCS to transmit signals uses the spectral efficiently. The simulation results validate the proposed algorithm and show that under the premise of meeting the target BER,the adaptive system performing the proposed algorithm has a higher average spectral efficiency ( ASE) than that of the non-adaptive system.

An adaptive pipelining scheme for H.264/AVC CABAC decoder

An adaptive pipelining scheme for H.264/AVC context-based adaptive binary arithmetic coding(CABAC) decoder for high definition(HD) applications is proposed to solve data hazard problems coming from the data dependencies in CABAC decoding process.An efficiency model of CABAC decoding pipeline is derived according to the analysis of a common pipeline.Based on that,several adaptive strategies are provided.The pipelining scheme with these strategies can be adaptive to different types of syntax elements(SEs) and the pipeline will not stall during decoding process when these strategies are adopted.In addition,the decoder proposed can fully support H.264/AVC high4:2:2 profile and the experimental results show that the efficiency of decoder is much higher than other architectures with one engine.Taking both performance and cost into consideration,our design makes a good tradeoff compared with other work and it is sufficient for HD real-time decoding.

Hop-by-hop Content Distribution with Network Coding in Multihop Wireless Networks

The predominant use of today＇s networks is content access and distribution. Network Coding （NC） is an innovative technique that has potential to improve the efficiency of multicast content distribution over multihop Wireless Mesh Networks （WMNs） by allowing intermediate Forwarding Nodes （FNs） to encode and then forward data packets. Practical protocols are needed to realize the benefits of the NC technique. However, the existing NC-based multicast protocols cannot accurately determine the minimum number of coded packets that a FN should send in order to ensure successful data delivery to the destinations, so that many redundant packets are injected into the network, leading to performance degradation. In this paper, we propose HopCaster, a novel reliable multicast protocol that incorporates network coding with hop-by-hop transport. HopCaster completely eliminates the need for estimating the number of coded packets to be transmitted by a FN, and avoids redundant packet transmissions. It also effectively addresses the challenges of heterogeneous mulficast receivers. Moreover, a cross-layer multicast rate adaptation mechanism is proposed, which enables HopCaster to optimize multicast throughput by dynamically adjusting wireless transmission rate based on the changes in the receiver population and channel conditions during the course of mulficasting a coded data chunk. Our evaluations show that HopCaster significantly outperforms the existing NC-based multicast protocols.

A Practical Adaptive TuCM Scheme for Rayleigh Flat Fading Channels

A practical adaptive turbo coded modulation (TuCM) scheme was proposed and its adaptive method was described. With some hardware considerations, a suboptimal optimization algorithm that the number of fading regions is variable was put forward. Furthermore, the cutoff fade depth of power adaptation was modified to reduce the interruption probability. The results show that the proposed adaptive TuCM comes within 3 dB of Rayleigh fading channel capacity, and exhibits about 3 dB power gain relative to the conventional adaptive trellis-coded modulation (TCM), and is easy to realize by hardware.

Pragmatic Approach to Adaptive Turbo Coded Modulation

This paper presents a pragmatic adaptive scheme for TuCM over slowly fading channels. The adaptive scheme employs a single turbo coded modulator composed of a variable-rate turbo encoder and a variable-rate variable-power MQAM for all fading regions, so it has an acceptable complexity to implement. The optimal adaptive TuCM scheme is determined subject to various system constraints. Simulations have been performed to measure the performance of the scheme for different parameters. It is shown that adopting both the turbo coded modulator and the transmit power achieves a performance within 2.5 dB of the fading channel capacity.

Fractal Block Coding:A New Method

Fractal image compression is a completely new method to compress images by searching and exploiting the self similarity of the whole image . Fractal Block Coding (FBC) is a practicable fractal coding scheme with annoying slow encoding speed . In this paper, we classify the image blocks by Classified Vector Quantization (CVQ) technique and present an Adaptive Block Truncation Coding (ABTC) scheme to process the midrange blocks in the image. By this method , we reduce the encoding time to one forty fifth comparing to ordinary FBC method with little change in compression ratio and a little decreased coded image quality.

AN ADAPTIVE FEC SCHEME FOR Ka-BAND SATELLITE COMMUNICATIONS

Rain attenuation is the major problem for Ka-band satellite communications, and the fading due to rain can be well described by a lognormally distributed, first-order auto regressive model. Forward Error-control Coding (FEC) techniques can be used to reduce the effect of the rain attenuation, but the use of FEC causes a reduction in the bandwidth efficiency.In order to increase the bandwidth efficiency as well as maintain high link availability, an Adaptive Forward Error-control Coding (AFEC) scheme with rain fading prediction is proposed and analyzed in this paper. The results show that AFEC offers a good trade-off between link availability and bandwidth efficiency.

A Bit-level Text Compression Scheme Based on the ACW Algorithm

This paper presents a description and performance evaluation of a new bit-level, lossless, adaptive, and asymmetric data compression scheme that is based on the adaptive character wordlength （ACW（n）） algorithm. The proposed scheme enhances the compression ratio of the ACW（n） algorithm by dividing the binary sequence into a number of subsequences （s）, each of them satisfying the condition that the number of decimal values （d） of the n-bit length characters is equal to or less than 256. Therefore, the new scheme is referred to as ACW（n, s）, where n is the adaptive character wordlength and s is the number of subsequences. The new scheme was used to compress a number of text files from standard corpora. The obtained results demonstrate that the ACW（n, s） scheme achieves higher compression ratio than many widely used compression algorithms and it achieves a competitive performance compared to state-of-the-art compression tools.

Research on Threshold Adjustment Algorithm in Adaptive Modulation and Coding

Adaptive Modulation and Coding （AMC） has gained a lot of attentions in the research of High Speed Downlink Packet Access （HSDPA）. The idea is to adapt the transmission to the fast changing channel conditions by the use of different Modulation and Coding Schemes （MCS）. This paper presents an adaptive AMC algorithm and introduces a theoretical analysis model in order to to investigate its throughput and Frame Error Rate （FER）. Subject to the given FER target, our numerical and link level simulation results both show that our algorithm outperforms other existing adaptive algorithms.

High throughput VLSI architecture for H.264/AVC context-based adaptive binary arithmetic coding(CABAC) decoding

Context-based adaptive binary arithmetic coding(CABAC) is the major entropy-coding algorithm employed in H.264/AVC.In this paper,we present a new VLSI architecture design for an H.264/AVC CABAC decoder,which optimizes both decode decision and decode bypass engines for high throughput,and improves context model allocation for efficient external memory access.Based on the fact that the most possible symbol(MPS) branch is much simpler than the least possible symbol(LPS) branch,a newly organized decode decision engine consisting of two serially concatenated MPS branches and one LPS branch is proposed to achieve better parallelism at lower timing path cost.A look-ahead context index(ctxIdx) calculation mechanism is designed to provide the context model for the second MPS branch.A head-zero detector is proposed to improve the performance of the decode bypass engine according to UEGk encoding features.In addition,to lower the frequency of memory access,we reorganize the context models in external memory and use three circular buffers to cache the context models,neighboring information,and bit stream,respectively.A pre-fetching mechanism with a prediction scheme is adopted to load the corresponding content to a circular buffer to hide external memory latency.Experimental results show that our design can operate at 250 MHz with a 20.71k gate count in SMIC18 silicon technology,and that it achieves an average data decoding rate of 1.5 bins/cycle.

Efficient VLSI architecture of CAVLC decoder with power optimized

This paper presents an efficient VLSI architecture of the contest-based adaptive variable length code （CAVLC） decoder with power optimized for the H.264/advanced video coding （AVC） standard. In the proposed design, according to the regularity of the codewords, the first one detector is used to solve the low efficiency and high power dissipation problem within the traditional method of table-searching. Considering the relevance of the data used in the process of runbefore＇s decoding, arithmetic operation is combined with finite state machine （FSM）, which achieves higher decoding efficiency. According to the CAVLC decoding flow, clock gating is employed in the module level and the register level respectively, which reduces 43% of the overall dynamic power dissipation. The proposed design can decode every syntax element in one clock cycle. When the proposed design is synthesized at the clock constraint of 100 MHz, the synthesis result shows that the design costs 11 300 gates under a 0.25 μm CMOS technology, which meets the demand of real time decoding in the H.264/AVC standard.

MCS Selection Criteria Based on Performance Simulation for HSDPA

An adaptive modulation and coding (AMC) scheme integrated with multi-code transmission for high speed downlink packet access is presented and some modulation and coding scheme (MCS) selection criteria are proposed to maximize single user data rates. Based on link-level performance analysis, the MCS selection criteria are proposed with the constraints of QoS requirement, modulation level, channel coding rate and the number of available channelization codes. By allowing multiple transmission parameters changing, these criteria make the scheme more flexible to time-varying mobile channel with comparatively low complexity through a look-up table method. The AMC scheme is sensitive to the changes of channel condition and can save the channelization codes in an applicable way by applying these criteria.