Pulse Amplitude Modulation Symbols Research Articles

An Effective Spatial Modulation Based Scheme for Indoor VLC Systems

We propose an enhanced spatial modulation (SM)-based scheme for indoor visible light communication systems. This scheme enhances the achievable throughput of conventional SM schemes by transmitting higher order complex modulation symbol, which is decomposed into three different parts. These parts carry the amplitude, phase, and quadrant components of the complex symbol, which are then represented by unipolar pulse amplitude modulation (PAM) symbols. Superposition coding is exploited to allocate a fraction of the total power to each part before they are all multiplexed and transmitted simultaneously, exploiting the entire available bandwidth. At the receiver, a two-step decoding process is proposed to decode the active light emitting diode index before the complex symbol is retrieved. It is shown that at higher spectral efficiency values, the proposed modulation scheme outperforms conventional SM schemes with PAM symbols in terms of average symbol error rate (ASER), and hence, enhancing the system throughput. Furthermore, since the performance of the proposed modulation scheme is sensitive to the power allocation factors, we formulated an ASER optimization problem and propose a sub-optimal solution using successive convex programming (SCP). Notably, the proposed algorithm converges after only few iterations, whilst the performance with the optimized power allocation coefficients outperforms both random and fixed power allocation.

Low-Complexity Spatial Modulation for IM/DD Optical Wireless Communications

A bipolar pulse amplitude modulation (PAM)-based optical spatial modulation transmission scheme is developed for intensity modulation/direct detection optical wireless communications. In the proposed scheme, multiple light emitting diodes (LEDs) and multiple photodiodes are employed at the transmitter and receiver, respectively. The transmit LEDs are divided into two groups. The first group of LEDs transmits the positive part of the PAM symbol, while the second group of LEDs transmits the absolute value of the negative part of the bipolar PAM symbol. Besides, spatial shift keying is employed in the active LED group to improve data rate. According to the transmit strategy, a novel low-complexity receiver algorithm is developed.

Optimization of Flexible Non-Uniform Multilevel PAM for Maximizing the Aggregated Capacity in PON Deployments

Non-uniform pulse amplitude modulation (PAM) utilizes unequal distances between its modulation levels. In a multilevel PAM symbol, multiple bits are encoded. Due to the unequal level spacing, some bits can be decoded successfully at a lower received optical power than others. This is well suited for practical passive optical network (PON) deployments wherein the optical powers received by the different optical network units (ONUs) typically vary over a broad range. Thus, more ONUs in the PON can successfully decode non-uniform PAM-4 and PAM-8 than standard PAM-4/8, thereby increasing the aggregated capacity of the network. In systems where signal-dependent noise makes up a significant part of the total received noise level, the non-uniform PAM constellation can be adapted to take this signal-dependent variance into account. In doing so, a lower unequal level spacing can be used, decreasing the received optical power required to successfully decode all the bits in the PAM symbol. The impact of non-uniform PAM on the network throughput is presented by comparison of the experimental results with the actual loss distribution of a commercially deployed PON.

Hellinger-Distance-Optimal Space Constellations

In this letter, we consider the space constellation design for a multi-input-multi-ouput optical wireless communication (MIMO-OWC) system equipped with a single photon avalanche diode receiver array (SPAD MIMO-OWC) in presence of log-normal fading. For conventional intensity modulated direct detection (IM/DD) MIMO-OWC with Gaussian noise, repetition code (RC), which transmits the same pulse amplitude modulation symbols, has been proved to be the diversity-optimal space-only constellation. However, different from IM/DD MIMO-OWC with Gaussian noise, the output of SPAD MIMO-OWC is Poisson distributed due to the photon-counting nature of SPADs. For such a system, the maximum likelihood function is difficult to provide a useful insight into energy-efficient signal designs. In this letter, we develop a vector-version Anscombe root transform-based receiver, for which the minimum Hellinger distance of transmitted constellation dominates the error performance. Then, an energy-efficient space constellation is attained by maximizing the worst case minimum Hellinger distance for a fixed average transmitted optical power within the non-negative orthants of a multidimensional space. Comprehensive simulations indicate that our proposed space constellation significantly outperforms RC, which is the best space constellation currently available for this system.

Universal soft demapper for M-ary PAM with reduced complexity

In this paper, we propose an efficient soft demapper for M-ary pulse amplitude modulation (PAM) schemes. The proposed demapper estimates soft decision bit information (SDBI) for any M-ary PAM symbols using a universal type of hardware structure. The proposed method performs as well as the Max-log method, without any exhaustive search process. Instead, it maps a detected PAM symbol to a specific region, with only one constellation symbol to estimate the distance. In this way, the proposed method requires approximately one distance estimation per bit. We first derive the equations to estimate SDBI for a few Gray-mapped M-ary PAM schemes, and subsequently present compact universal equations applicable to any M-ary PAM scheme. The simulation results confirm that the proposed method produces exactly the same performance as the Max-log method with greatly reduced computational complexity.

A Soft Decode–Compress–Forward Relaying Scheme for Cooperative Wireless Networks

This paper proposes a new technique for soft information relaying, which is based on a soft decode–compress–forward relay protocol. The proposed system provides a means of using distributed low-density parity-check (LDPC) coding in conjunction with higher order modulation, such as pulse amplitude modulation (PAM) and quadrature amplitude modulation (QAM), which is effective even under poor source–relay link conditions. Ordinarily, such schemes suffer from error propagation to the destination caused by incorrect decoding at the relay when the signal-to-noise ratio (SNR) on the source–relay link is low; however, our system avoids this problem by generating soft versions of the additional (parity-bearing) PAM symbols for transmission from the relay. The proposed technique of soft compression does not suffer from parity log-likelihood ratios (LLRs) converging to zero, as do many soft re-encoding techniques for turbo and LDPC codes. In the case of Gray-coded PAM/QAM signaling, we also propose a method of performing exact expectation-based soft modulation with low computational complexity. Furthermore, we propose a new model, which we refer to as the soft scalar model, for the overall source-to-destination channel encountered by the constellation symbols, and this model is used at the destination to compute LLRs for joint decoding of the distributed LDPC code. Simulation results demonstrate that the proposed scheme can provide good coding gain, diversity gain, and spectral efficiency under poor source–relay SNR conditions.

Low-Complexity LLR Calculation for Gray-Coded PAM Modulation

Higher-order modulation schemes are employed to improve the spectral efficiency in modern communication systems. However, the conventional Max-Log-MAP symbol-to-bit demapper suffers from a large computational burden. To cope with this problem, this letter proposes a novel log-likelihood ratio computation algorithm for Gray-coded higher-order pulse-amplitude modulation (PAM). The proposed method reduces the order of complexity from $O(2^M) $ to $O(M)$ without any difference of the LLR values compared with the Max-Log-MAP demapper, where $M$ is the number of bits in one PAM symbol. Moreover, it is also shown that the proposed algorithm achieves superior complexity reduction compared with a recently proposed low-complexity demapper.

Subspace-Based Blind Channel Estimation by Separating Real and Imaginary Symbols for Cyclic-Prefixed Single-Carrier Systems

Blind channel estimation based on a subspace-based algorithm for single-input single-output cyclic-prefixed single-carrier systems is proposed in this brief. The proposed method is different from conventional subspace-based approaches, which exploit the original complex structure of the received data symbols. In contrast, we separate the real part and the imaginary part of the received complex symbols and then exploit these two kinds of symbols to construct the signal model. The noise subspace can then be established to estimate the channel impulse response (CIR) using a subspace algorithm when real symbols, such as binary phase shift keying or pulse amplitude modulation symbols, are applied. The real part and the imaginary part of the CIR can be estimated individually and simultaneously with only a sign ambiguity. With the aid of repetition index, the proposed method is workable even if few data blocks are available. Simulation results demonstrate that the proposed approach outperforms conventional methods in normalized mean-squared error under static channel environments.