Uncoded Channel Research Articles

Experimental evaluation of a linear angular momentum multiplexed radio link for moving platforms.

Linear angular momentum multiplexing (LAMM) has recently been proposed for high spectral-efficiency communications between moving platforms, such as between trains and ground infrastructure. We present performance results obtained from a scale experimental system comprising a 2 × 2 antenna system operating at 2.35 GHz. The link transmitted two independent video streams, using RF pre-coding and software-defined radios to modulate and up/down-convert the signals. Linear motion is introduced to demonstrate the translation-invariance of the technique. We interpret the measured data with the aid of an analytical model to show that crosstalk between the two channels is at levels low enough to consistently support the video streams without interruption. Specifically, our results show spectral efficiency is consistently higher when LAMM coding is enabled compared with an uncoded channel.

Soft-output maximum-likelihood detector for quadrature spatial modulation

Spatial modulation (SM) presents a pragmatic approach for transmitting information, where the modulator uses well known amplitude/phase modulation (APM) techniques such as phase shift keying (PSK) and quadrature amplitude modulation (QAM), but also employs the antenna index to convey additional information. Nevertheless, the spectral efficiency of SM can be further improved. On this note, to further enhance the spectral efficiency of SM, quadrature SM (QSM) modulation was proposed. In coded channels, therefore, typically soft-output detection coupled with soft-input channel decoding yields significant signal-to-noise ratio (SNR) gain. Hence, in this paper, soft-output maximum-likelihood detector (SOMLD) for QSM modulated system is proposed. Monte Carlo simulation results demonstrate that there is a close agreement between the error performances of the proposed SOMLD scheme and those of its hard-decision maximum-likelihood detector counterpart in uncoded channels, while significant signal-to-noise ratio (SNR) gains are yielded in coded channels. Keywords: Multiple-input multiple-output, quadrature spatial modulation, soft-output detection, space shift keying, spatial modulation

Detection of GSM and GSSK Signals with Soft-Output Demodulators

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

Soft‐output space‐time block coded spatial modulation

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

Base Station Cooperation With Feedback Optimization: A Large System Analysis

In this paper, we study feedback optimization problems that maximize the users' signal to interference plus noise ratio (SINR) in a two-cell multiple-input multiple-output broadcast channel. Assuming the users learn their direct and interfering channels perfectly, they can feed back this information to the base stations (BSs) over the uplink channels. The BSs then use the channel information to design their transmission scheme. Two types of feedback are considered: 1) analog and 2) digital. In the analog feedback case, the users send their unquantized and uncoded channel state information (CSI) over the uplink channels. In this context, given a user's fixed transmit power, we investigate how he/she should optimally allocate it to feed back the direct and interfering (or cross) CSI for two types of BS cooperation schemes, namely, multicell processing (MCP) and coordinated beamforming. In the digital feedback case, the direct and cross link channel vectors of each user are quantized separately, each using the random vector quantization scheme, with different size codebooks. The users then send the index of the quantization vector in the corresponding codebook to the BSs. Similar to the feedback optimization problem for the analog feedback, we investigate the optimal bit partitioning for the direct and interfering link for both types of cooperation. We focus on regularized channel inversion precoding structures and perform our analysis in the large system limit in which the number of users per cell $(K)$ and the number of antennas per BS $(N)$ tend to infinity with their ratio $\beta=({K}/{N})$ held fixed. We show that for both types of cooperation, for some values of interfering channel gain, usually at low values, no cooperation between the BSs is preferred. This is because, for these values of cross channel gain, the channel estimates for the cross link are not accurate enough for their knowledge to contribute to improving the SINR and there is no benefit in doing BS cooperation under that condition. We also show that for the MCP scheme, unlike in the perfect CSI case, the SINR improves only when the interfering channel gain is above a certain threshold.

Performance of Linear Block Coding for Multipath Fading Channel

This paper deals with the performance of linear block codes which provide a new paradigm for transmission over multipath fading channels. Multi path channel fading is the main enemy for any wireless communications system. Therefore, for any novel approach applied at any wireless communication system, its efficiency is measured according to its ability of mitigating the distortion caused by fading. It causes time dispersion to the transmitted symbols resulting in inter symbol interference (ISI). ISI inter symbol interference problem is a major impairment of the wireless communication channel. To mitigate the ISI problem and to have reliable communications in wireless channel, channel equalizer and channel coding technique is often employed. In this paper the BER (Bit Error Rate) performance is shown from analytically and by means of simulation for multipath dispersive channels. We have designed a channel equalizer using MLSE (Viterbi algorithm) in this paper for such a multipath channel (introducing inter symbol interferences) with BPSK modulation based on the assumption that the channel can be perfectly estimated at the receiver. Obviously the performance of channel coding in terms of BER is better than uncoded channel. Index Terms—BER, BPSK, Linear block code, SNR, Viterbi algorithm, Maximum-likelihood sequence estimator (MLSE), ISI.

Self‐Calibrated Energy‐Efficient and Reliable Channels for On‐Chip Interconnection Networks

Energy‐efficient and reliable channels are provided for on‐chip interconnection networks (OCINs) using a self‐calibrated voltage scaling technique with self‐corrected green (SCG) coding scheme. This self‐calibrated low‐power coding and voltage scaling technique increases reliability and reduces energy consumption simultaneously. The SCG coding is a joint bus and error correction coding scheme that provides a reliable mechanism for channels. In addition, it achieves a significant reduction in energy consumption via a joint triplication bus power model for crosstalk avoidance. Based on SCG coding scheme, the proposed self‐calibrated voltage scaling technique adjusts voltage swing for energy reduction. Furthermore, this technique tolerates timing variations. Based on UMC 65 nm CMOS technology, the proposed channels reduces energy consumption by nearly 28.3% compared with that for uncoded channels at the lowest voltage. This approach makes the channels of OCINs tolerant of transient malfunctions and realizes energy efficiency.

Application of MTR soft-decision decoding in multiple-head magnetic recording systems

Application of a simple approach for the soft-decision decoding of Maximum-Transition-Run (MTR) codes has been presented in this paper. A lowdemanded hardware realization have been proposed for soft-decision decoding in MTR basic AND, OR and XOR logic circuits. The suggested approach is explored over the two-track, two-head E2PR4 partial response magnetic recording system. The overall two-track channel detection complexity reduction of 41·9% is offered in simulation scheme, encoded by Low-Density Parity-Check (LDPC) code, serially concatenated with inner MTR. The 1·9 dB coding gain has been obtained, comparing to uncoded channel and assuming the AWGN noise presence.

Multitrack Digital Data Storage: A Reduced Complexity Architecture

We describe a low-complexity noniterative detector for magnetic and optical multitrack high-density data storage. The detector is based on the M-algorithm architecture. It performs limited breadth-first detection on the equivalent one-dimensional (1-D) channel obtained by column-by-column helical unwinding of the two-dimensional (2-D) channel. The detection performance is optimized by the use of a specific 2-D minimum-phase factorization of the channel impulse response by the equalizer. An optimized path selection scheme maintains the complexity close to practical 1-D Viterbi. This scheme is based on an approximate path metric parallel sort network, taking advantage of the metrics' residual ordering from previous M-algorithm iterations. Such an architecture approaches maximum-likelihood performance on a high areal density uncoded channel for a practical number of retained paths M and bit error rate (BER) below 10-4. The performance of the system is evaluated when the channel is encoded with multi-parity check (MPC) block inner code and an outer interleaved Reed-Solomon code. The inner code enhances the minimum error distance of the equalized channel and reduces the correct path losses of the M-algorithm path buffer. The decoding is performed noniteratively. Here, we compare the performance of the system to the soft iterative joint decoding of the read channels for data pages encoded with low-density parity check (LDPC) codes with comparable rates and block length. We provide an approximation of the 2-D channel capacity to further assess the performance of the system

Finite-Dimensional Bounds on ${\BBZ}_m$ and Binary LDPC Codes With Belief Propagation Decoders

This paper focuses on finite-dimensional upper and lower bounds on decodable thresholds of Zopf <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sub> and binary low-density parity-check (LDPC) codes, assuming belief propagation decoding on memoryless channels. A concrete framework is presented, admitting systematic searches for new bounds. Two noise measures are considered: the Bhattacharyya noise parameter and the soft bit value for a maximum a posteriori probability (MAP) decoder on the uncoded channel. For Zopf <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sub> LDPC codes, an iterative m-dimensional bound is derived for m-ary-input/symmetric-output channels, which gives a sufficient stability condition for Zopf <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sub> LDPC codes and is complemented by a matched necessary stability condition introduced herein. Applications to coded modulation and to codes with nonequiprobably distributed codewords are also discussed. For binary codes, two new lower bounds are provided for symmetric channels, including a two-dimensional iterative bound and a one-dimensional noniterative bound, the latter of which is the best known bound that is tight for binary-symmetric channels (BSCs), and is a strict improvement over the existing bound derived by the channel degradation argument. By adopting the reverse channel perspective, upper and lower bounds on the decodable Bhattacharyya noise parameter are derived for nonsymmetric channels, which coincides with the existing bound for symmetric channels

Unquantized and uncoded channel state information feedback in multiple-antenna multiuser systems

We propose a channel state information (CSI) feedback scheme based on unquantized and uncoded (UQ-UC) transmission. We consider a system where a mobile terminal obtains the downlink CSI and feeds it back to the base station using an uplink feedback channel. If the downlink channel is an independent Rayleigh fading channel, then the CSI may be viewed as an output of a complex independent identically distributed Gaussian source. Further, if the uplink feedback channel is an additive white Gaussian noise channel, and the downlink CSI is perfectly known at the mobile terminal, it can be shown that UQ-UC CSI transmission (that incurs zero delay) is optimal in that it achieves the same minimum mean-squared error distortion as a scheme that optimally (in the Shannon sense) quantizes and encodes the CSI, while theoretically incurring infinite delay. Since the UQ-UC transmission is suboptimal on correlated wireless channels, we propose a simple linear CSI feedback receiver that can be used to improve the performance of UQ-UC transmission while still retaining the attractive zero-delay feature. We provide bounds on the performance of such UQ-UC CSI feedback and study its impact on the achievable information rates. Furthermore, we explore its application and performance in multiple-antenna multiuser wireless systems, and also propose a corresponding pilot-assisted channel-state estimation scheme

A new ML detection algorithm for Orthogonal Multicode system in Nakagami fading channel

Based on the Maximum-Likelihood (ML) criterion, this paper proposes a novel noncoherent detection algorithm for Orthogonal Multicode (OM) system in Nakagami fading channel. Some theoretical analysis and simulation results are presented. It is shown that the proposed ML algorithm is at least 0.7 dB better than the conventional Matched-Filter (MF) algorithm for uncoded systems, in both non-fading and fading channels. For the consideration of practical application, it is further simplified in complexity. Compared with the original ML algorithm, the simplified ML algorithm can provide significant reduction in complexity with small degradation in performance.

Analysis and Design of Short Block OFDM Spreading Matrices for Use on Multipath Fading Channels

We consider the use of block spreading in a multicarrier system to gain diversity advantage when employed over multipath fading channels. The main idea is to split the full set of subcarriers into smaller blocks and spread the data symbols across these blocks via unitary spreading matrices in order to gain multipath diversity across each block at the receiver. We pose the problem of designing the spreading matrix as a finite dimensional optimization problem in which the asymptotic error is minimized. This formulation allows us to find explicit solutions for the optimal spreading matrices. The performance is validated for the uncoded channel as well as for the coded channel employing turbo-iterative decoding. We further demonstrate that suboptimal linear complexity equalization strategies for spread orthogonal frequency division multiplexing (OFDM) do not gain any diversity advantage over traditional diagonal OFDM.

Approximate Belief Propagation, Density Evolution, and Statistical Neurodynamics for CDMA Multiuser Detection

We present a theory to analyze the performance of the parallel interference canceller (PIC) for code-division multiple-access (CDMA) multiuser detection, applied to a randomly spread, fully synchronous baseband uncoded CDMA channel model with additive white Gaussian noise under perfect power control in the large-system limit. We reformulate PIC as an approximation to the belief propagation algorithm for the detection problem. We then apply the density evolution framework to analyze its detection dynamics. It turns out that density evolution for PIC is essentially the same as statistical neurodynamics, a theory to describe dynamics of a certain type of neural network model. Adopting this correspondence, we develop the density evolution framework for PIC using statistical neurodynamics. The resulting formulas, however, are only approximately correct for describing detection dynamics of PIC even in the large-system limit, because we ignore the Onsager reaction terms in the derivation. We then propose a modified PIC algorithm, in which we subtract the Onsager reaction terms algorithmically, for which the density evolution formulas give a correct description of the detection dynamics in the large-system limit.

Constrained coding for binary channels with high intersymbol interference

Partial-response (PR) signaling is used to model communications channels with intersymbol interference (ISI) such as the magnetic recording channel and the copper-wire channel for digital subscriber lines. Coding for improving noise immunity in higher order partial-response channels, such as the extended class-4 channels denoted EPR4, E/sup 2/PR4, E/sup 3/PR4, has become an important subject as the linear densities in magnetic recording approach those at which these partial-response channels are the best models of real channels. In this paper, we consider partial-response channels for which ISI is so severe that the channels fail to achieve the matched-filter bound (MFB) for symbol error rate, assuming maximum-likelihood decoding. We show that their performance can be improved to the MFB by high-rate codes based on constrained systems, some of which may even simplify the Viterbi (1979) detectors relative to the uncoded channels. We present several examples of high-rate constrained codes for E/sup 2/PR4 and E/sup 3/PR4 channels and evaluate their performance by simulation.

On Viterbi detector path metric differences

This letter continues the investigation of methods for computing exact bounds on the path metric differences in maximum-likelihood sequence detectors based upon the Viterbi algorithm. New upper and lower estimates for these bounds are presented and recast in terms of a collection of linear programming problems. These estimates improve upon previously proposed linear programming bounds. The estimates are applied to derive exact bounds or provably close to exact bounds for several Viterbi detectors corresponding to coded and uncoded partial-response channels of practical interest in digital magnetic and optical recording.

Coding to improve SNR in magnetic recording

The magnetic recording channel is often equalised to the PR4 partial response. Viterbi detection is used to detect the recorded data, but suffers a loss owing to the effects of noise correlation. The use of coding on the PR4 magnetic recording channel to reduce the effects of noise correlation is proposed. This is shown to achieve a gain in effective SNR over an uncoded channel. Parity codes are shown to be one method of achieving this. The read data is decoded with a soft decision Viterbi detector. The performance of the method is verified through simulations.

Capacity of channels with uncoded side information

AbstractParallel independent channels where no encoding is allowed for one of the channels are studied. The Slepian‐Wolf theorem on source coding of correlated sources is used to show that any information source whose entropy rate is below the sum of the capacity of the coded channel and the input/output mutual information of the uncoded channel is transmissible with arbitrary reliability. The converse is also shown. Thus, coding of the side information channel is unnecessary when its mutual information is maximized by the source distribution. Applications to superposed coded/uncoded transmission on Gaussian channels are studied and an information‐theoretic interpretation of Parallel‐Concatenated channel codes and, in particular. Turbo codes is put forth.

Uncoded and coded performance of MFSK and DPSK in Nakagami fading channels

The author presents uncoded and coded performance results for noncoherent M-ary frequency-shift keying (MFSK) and differentially coherent binary phase-shift keying (DPSK) in a slow nonselective Nakagami-m (1960) fading channel. He gives simple expressions for the asymptotic slopes of probability of bit error for large signal-to-noise ratio and shows that the effective order of diversity compared to an uncoded Rayleigh channel is the product of two parameters, one for the channel and one for the code. He also compares the uncoded Nakagami-m results to those of the Rician channel in order to show performance differences between these two generalized fading channel models. >

Soft-Output Decision-Based Detection of SSK, BI-SSK and QSM

Space shift keying (SSK) modulation is a special case of conventional spatial modulation (SM), where the amplitude and/or phase modulation symbols are eliminated from the transmission process so as to reduce complexity. However, high spectral efficiencies are difficult to achieve with SSK. At the same time, the spectral efficiency of SM can be further improved. On this note, to further enhance the spectral efficiencies of both SM and SSK, quadrature SM (QSM) and Bi-SSK modulations, respectively, were proposed. In coded channels, typically soft-output detection coupled with soft-input channel decoding yields significant signal-to-noise ratio (SNR) gain. Hence, in this paper, we propose soft-output maximum-likelihood detectors (SOMLD) for SSK, Bi-SSK and QSM modulated systems. Monte Carlo simulation results demonstrate that the error performances of the proposed SOMLD schemes closely match with that of their hard-decision maximum-likelihood detector counterparts in uncoded channels; while, significant SNR gains are yielded in coded channels.