In the source coding problem with cost constraint, a cost function is defined over the code alphabet. This can be regarded as a noiseless channel coding problem with cost constraint. In this case, we will not distinguish between the input alphabet and the output alphabet of the channel. However, we must distinguish them for a noisy channel. In the channel coding problem with cost constraint so far, the cost function is defined over the input alphabet of the noisy channel. In this paper, we define the cost function over the output alphabet of the channel. And, the cost is paid only after the received word is observed. Note that the cost is a random variable even if the codeword is fixed. We show the channel capacity with cost constraint defined over the output alphabet. Moreover, we generalize it to tolerate some decoding error and some cost overrun. Finally, we show that the cost constraint can be described on a subset of arbitrary set which may have no structure.

Mobile video traffic is expected to increase explosively because of the proliferating number of Wi-Fi terminals. An overloaded multiple-input multiple-output (MIMO) technique allows the receiver to implement smaller number of antennas than the transmitter in exchange for degradation in video quality and a large amount of computational complexity for postcoding at the receiver side. This paper proposes a novel linear precoder for high-quality video streaming in overloaded multiuser MIMO systems, which protects visually significant portions of a video stream. A low complexity postcoder is also proposed, which detects some of data symbols by linear detection and the others by a prevoting vector cancellation (PVC) approach. It is shown from simulation results that the combination use of the proposed precoder and postcoder achieves higher-quality video streaming to multiple users in a wider range of signal-to-noise ratio (SNR) than a conventional unequal error protection scheme. The proposed precoder attains 40dB in peak signal-to-noise ratio even in poor channel conditions such as the SNR of 12dB. In addition, due to the stepwise acquisition of data symbols by means of linear detection and PVC, the proposed postcoder reduces the number of complex additions by 76% and that of multiplications by 64% compared to the conventional PVC.

This paper considers a joint channel coding and random number generation from the channel output. Specifically, we want to transmit a message to a receiver reliably and at the same time the receiver extracts pure random bits independent of the channel input. We call this problem as the joint channel coding and intrinsic randomness problem. For general channels, we clarify the trade-off between the coding rate and the random bit rate extracted from the channel output by using the achievable rate region, where both the probability of decoding error and the approximation error of random bits asymptotically vanish. We also reveal the achievable rate regions for stationary memoryless channels, additive channels, symmetric channels, and mixed channels.

The 1-bit digital radio frequency (DRF) transmitter using a band-pass delta-sigma modulator (BP-DSM) can output a radio frequency (RF) signal carrying a binary data stream with a constant data rate regardless of the carrier frequency, which makes it possible to transmit RF signals over digital optical links with a constant bit rate. However, the optical link requires a line coding, such as 8B10B or 64B66B, to constrain runlength and disparity, and the line coding corrupts the DRF power spectrum owing to additional or encoded data. This paper proposes a new line coding for BP-DSM, which is able to control the runlength and the disparity of the 1-bit data stream by adding a notch filter to the BP-DSM that suppresses the low frequency components. The notch filter stimulates the data change and balances the direct current (DC) components. It is demonstrated that the proposed line coding shortens the runlength from 50 bits to less than 8 bits and reduces the disparity from several thousand bits to 5 bits when the 1-bit DRF transmitter outputs an LTE signal with 5 MHz bandwidth, when using carrier frequencies from 0.5GHz to 2GHz and an output power variation of 60dB.

High-resolution image and video communication in home networks is highly expected to proliferate with the spread of Wi-Fi devices and the introduction of multiple-input multiple-output (MIMO) systems. This paper proposes a joint transmission and coding scheme for broadcasting high-resolution video streams over multiuser MIMO systems with an eigenbeam-space division multiplexing (E-SDM) technique. Scalable video coding makes it possible to produce the code stream comprised of multiple layers having unequal contribution to image quality. The proposed scheme jointly assigns the data of scalable code streams to subcarriers and spatial streams based on their signal-to-noise ratio (SNR) values in order to transmit visually important data with high reliability. Simulation results show that the proposed scheme surpasses the conventional unequal power allocation (UPA) approach in terms of both peak signal-to-noise ratio (PSNR) of received images and correct decoding probability. PSNR performance of the proposed scheme exceeds 35dB with the probability of over 95% when received SNR is higher than 6dB. The improvement in average PSNR by the proposed scheme compared to the conventional UPA comes up to approx. 20dB at received SNR of 6dB. Furthermore, correct decoding probability reaches 95% when received SNR is greater than 4dB.

This paper presents the performance of outer-loop control for selecting the best modulation and coding scheme (MCS) based on mutual information (MI) for orthogonal frequency division multiplexing (OFDM) multiple-input multiple-output (MIMO) spatial division multiplexing (SDM). We propose an outer-loop control scheme that updates the measured MI per information bit value for selecting the best MCS from a mapping table that associates the block error rate (BLER) and MI per bit instead of directly updating the MCS selection threshold so that the required BLER is satisfied. The proposed outer-loop control is applicable to continuous data transmission including intermittent transmission with a short blank period. Moreover, we compare the measured BLER and throughput performance for two types of outer-loop control methods: instantaneous block error detection and moving-average BLER detection. In the paper, we use maximum likelihood detection (MLD) for MIMO SDM. Computer simulation results optimize the step size for the respective outer-loop control schemes for selecting the best MCS that achieves the higher throughput and the target BLER simultaneously. Computer simulation results also show that by using the most appropriate step size, the outer-loop control method based on the instantaneous block error detection of each physical resource block is more appropriate than that based on the moving-average BLER detection from the viewpoints of achieving the target BLER more accurately and higher throughput.

In holographic data storage, information is recorded within the volume of a holographic medium. Typically, the data is presented as an array of pixels with modulation in amplitude and/or phase. In the 4-f orientation, the Fourier domain representation of the data array is produced optically, and this image is recorded. If the Fourier image contains large peaks, the recording material can saturate, which leads to errors in the read-out data array. In this paper, we present a coding process that produces sparse ternary data arrays. Ternary modulation is used because it inherently provides Fourier domain smoothing and allows more data to be stored per array in comparison to binary modulation. Sparse arrays contain fewer on-pixels than dense arrays, and thus contain less power overall, which reduces the severity of peaks in the Fourier domain. The coding process first converts binary data to a sequence of ternary symbols via a high-rate block code, and then uses guided scrambling to produce a set of candidate codewords, from which the most sparse is selected to complete the encoding process. Our analysis of the guided scrambling division and selection processes demonstrates that, with primitive scrambling polynomials, a sparsity greater than 1/3 is guaranteed for all encoded arrays, and that the probability of this worst-case sparsity decreases with increasing block size.

In order to obtain higher diversity gain, the use of additional resources such as time, frequency, and/or antennas are necessary. The aim of this study is to achieve adequate temporal diversity gain without needing additional resources beyond decoding delay and decoding complexity. If the channel state information (CSI) is not available at the transmitter side, the transmitter sends information at a given constant transmission rate while the channel capacity varies according to the channel state. If the instantaneous channel capacity is greater than the given transmission rate, the system can successfully transmit information but it does not exploit the entire available channel capacity. We focus on this extra channel capacity to transmit other information based on a joint network-channel coding in order to obtain higher diversity and coding gains. This paper provides the basic concept of the transmit diversity with the joint network-channel coding and investigates its performances in terms of outage probability, additional decoding delay and complexity, and frame-error rate (FER).

This paper proposes an enhancement to a previously reported adaptive peak-to-average power ratio (PAPR) reduction method based on clipping and filtering (CF) for eigenmode multiple-input multiple-output (MIMO) — orthogonal frequency division multiplexing (OFDM) signals. We enhance the method to accommodate the case with adaptive modulation and channel coding (AMC). Since the PAPR reduction process degrades the signal-to-interference and noise power ratio (SINR), the AMC should take into account this degradation before PAPR reduction to select accurately the modulation scheme and coding rate (MCS) for each spatial stream. We use the lookup table-based prediction of SINR after PAPR reduction, in which the interference caused by the PAPR reduction is obtained as a function of the stream index, frequency block index, clipping threshold for PAPR reduction, and input backoff (IBO) of the power amplifier. Simulation results show that the proposed PAPR reduction method increases the average throughput compared to the conventional CF method for a given adjacent channel leakage power ratio (ACLR) when we assume practical AMC.

In this letter, functional duality between distributed source coding (DSC) with correlated messages and broadcast channel coding (BCC) with correlated messages is considered. It is shown that under certain conditions, for a given DSC problem with correlated messages, a functional dual BCC problem with correlated messages can be obtained, and vice versa. That is, the optimal encoder-decoder mappings for one problem become the optimal decoder-encoder mappings for the dual problem. Furthermore, the correlation structure of the messages in the two dual problems and the source distortion and channel cost measure for this duality are specified.

This paper investigates the performance of a combination of the affine encoder and the maximum mutual information decoder for symmetric channels, and proves that the random coding error exponent can be attained by this combination even if the conditional probability of the symmetric channel is not known to the encoder and decoder. This result clarifies that the restriction of the encoder to the class of affine encoders does not affect the asymptotic performance of the universal code for symmetric channels.

This work first investigates two existing check node unit (CNU) architectures for LDPC decoding: self-message-excluded CNU (SME-CNU) and two-minimum CNU (TM-CNU) architectures, and analyzes their area and timing complexities based on various realization approaches. Compared to TM-CNU architecture, SME-CNU architecture is faster in speed but with much higher complexity for comparison operations. To overcome this problem, this work proposes a novel systematic optimization algorithm for comparison operations required by SME-CNU architectures. The algorithm can automatically synthesize an optimized fast comparison operation that guarantees a shortest comparison delay time and a minimized total number of 2-input comparators. High speed is achieved by adopting parallel divide-and-conquer comparison operations, while the required comparators are minimized by developing a novel set construction algorithm that maximizes shareable comparison operations. As a result, the proposed design significantly reduces the required number of comparison operations, compared to conventional SME-CNU architectures, under the condition that both designs have the same speed performance. Besides, our preliminary hardware simulations show that the proposed design has comparable hardware complexity to low-complexity TM-CNU architectures.

Some statistical characteristics, including the means and the cross-correlations, of frequency-selective Rician fading channels seen by orthogonal frequency division multiplexing (OFDM) subcarriers are derived in this paper. Based on a pairwise error probability analysis, the mean vector and the cross-correlation matrix are used to obtain an upper bound of the overall bit-error rate (BER) in a closed-form for coded OFDM signals with and without inter-carrier interference. In this paper, the overall BER is defined as the average BER of OFDM signals of all subcarriers obtained by considering their cross-correlations. Numerical examples are presented to compare the proposed upper bound of the overall BERs and the overall BERs obtained by simulations.

Joint source-channel coding (JSCC) is a method to jointly allocate the given total transmission bitrate to the source coding and channel coding to maximize the video quality at the receiving end. In this paper, we propose a practical model for efficiently determining a near-optimal code rate for JSCC in real-time video communications. The conventional code rate decision schemes using analytical source coding distortion model and channel-induced distortion model are usually complex, and typically employ the process of model parameter training which involves potentially high computational complexity and implementation cost. To avoid the complex modeling procedure, we introduce a very simple video quality model based on the playable bitrate which is defined as the total bit amount per unit time that is not affected by the channel loss during transmission including correctly recovered bits by the channel decoder. Because the video quality at the receiving end is clearly commensurate with the playable bitrate, we can easily determine the quality-oriented near-optimal code rate by finding the code rate that maximizes the playable bitrate at the sender side. The proposed playable bitrate model is very simple because it does not require the complex training procedure for obtaining model parameters, which is usually required in the conventional code rate decision method. It is shown by simulations that the proposed code rate decision scheme based on the playable bitrate model can efficiently determine the near-optimal code rate for JSCC in terms of high accuracy on the optimal code rate.

In this work, a high performance LDPC decoder architecture is presented. It is a partially-parallel architecture for low-complexity consideration. In order to eliminate the idling time and hardware complexity in conventional partially-parallel decoders, the decoding process, decoder architecture and memory structure are optimized. Particularly, the parity-check matrix is optimally partitioned into four unequal sub-matrices that lead to high efficiency in hardware sharing. As a result, it can handle two different codewords simultaneously with 100% hardware utilization. Furthermore, for minimizing the performance loss due to round-off errors in fixed-point implementations, the well-known modified min-sum decoding algorithm is enhanced by our recently proposed high-performance CMVP decoding algorithm. Overall, the proposed decoder has high throughput, low complexity, and good BER performances. In the circuit implementation example of the (576,288) parity check matrix for IEEE 802.16e standard, the decoder achieves a data rate of 5.5 Gbps assuming 10 decoding iterations and 7 quantization bits, with a small area of 653 K gates, based on UMC 90 nm process technology.

We propose a simplified model of real-time joint source-channel coding, which can be used to adaptively determine the quality-optimal code rate of forward error correction (FEC) coding. The objective is to obtain the maximum video quality in the receiver, while taking time-varying packet loss into consideration. To this end, we propose a simplified model of the threshold set of the residual video packet loss rate (RVPLR). The RVPLR is the rate of residual loss of video packets after channel decoding. The threshold set is defined as a set of discrete RVPLRs in which the FEC code rate must be changed in order to maintain minimum distortion during increases or decreases of channel packet loss. Because the closed form of the proposed model is very simple and has one scene-dependent model parameter, a video sender can be easily implemented with the model. To train the scene-dependent model parameters in real-time, we propose a test-run method. This method accelerates the test-run while remaining sufficiently accurate for training the scene-dependent model parameters. By using the proposed model and test-run, the video sender can always find the optimal code rate on the fly whenever there is a change in the packet loss status in the channel. An experiment shows that the proposed model and test-run can efficiently determine the near-optimal code rate in joint source-channel coding.

This paper proposes a joint source-channel coding technology to transmit periodic vital information such as an electrocardiogram. There is an urgent need for a ubiquitous medical treatment space in which personalized medical treatment is automatically provided based on measured vital information. To realize such treatment and reduce the constraints on the patient, wireless transmission of vital information from a sensor device to a data aggregator is essential. However, the vital information has to be correctly conveyed through wireless channels. In addition, sensor devices are constrained by their battery power. Thus, a coding technique that provides robustness to noise, channel efficiency and low power consumption at encoding is essential. This paper presents a coding method that uses correlation of periodic vital information in the time domain, and provides a decoding scheme that uses the correlation as side information in a maximum a posteriori probability algorithm. Our results show that the proposed method provides better performance in terms of mean squared error after decoding in comparison to differential pulse-code modulation, and the uncoded case.

This paper addresses the relationships between diversity techniques and channel coding rates for OFDM systems. While a low channel coding rates is required if cyclic delay diversity is applied, the necessity of a low channel coding rate is alleviated with space time block coding.

The joint source-channel coding problem is considered. The joint source-channel coding theorem reveals the existence of a code for the pair of the source and the channel under the condition that the error probability is smaller than or equal to ε asymptotically. The separation theorem guarantees that we can achieve the optimal coding performance by using the two-stage coding. In the case that ε = 0, Han showed the joint source-channel coding theorem and the separation theorem for general sources and channels. Furthermore the ε-coding theorem (0 ≤ ε <1) in the similar setting was studied. However, the separation theorem was not revealed since it is difficult in general. So we consider the separation theorem in this setting.

A channel code is constructed using sparse matrices for stationary memoryless channels that do not necessarily have a symmetric property like a binary symmetric channel. It is also shown that the constructed code has the following remarkable properties. 1. Joint source-channel coding: Combining channel code with lossy source code, which is also constructed by sparse matrices, a simpler joint source-channel code can be constructed than that constructed by the ordinary block code. 2. Universal coding: The constructed channel code has a universal property under a specified condition.