One-Bit Massive MIMO: Channel Estimation and High-Order Modulations

We investigate the information-theoretic throughout achievable on a fading communication link when the receiver is equipped with one-bit analog-to-digital converters (ADCs). The analysis is conducted for the setting where neither the transmitter nor the receiver have a priori information on the realization of the fading channels. This means that channel-state information needs to be acquired at the receiver on the basis of the one-bit quantized channel outputs. We show that least-squares (LS) channel estimation combined with joint pilot and data processing is capacity achieving in the single-user, single-receive-antenna case. We also investigate the achievable uplink throughput in a massive multiple-input multiple-output system where each element of the antenna array at the receiver base-station feeds a one-bit ADC. We show that LS channel estimation and maximum-ratio combining are sufficient to support both multiuser operation and the use of high-order constellations. This holds in spite of the severe nonlinearity introduced by the one-bit ADCs

Design guidelines for spatial modulation

A new class of low-complexity, yet energyefficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO) has emerged. These systems are capable of exploiting the spatial dimensions (i.e. the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication whilst relying on a single-Radio Frequency (RF) chain. Moreover, SM may also be viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/ cooperative protocol design issues, and on their meritorious variants

Interference Aspects of Adaptive Modems over Slow Rayleigh Fading Channels

Adaptive modulation can achieve channel capacity gains by adapting the number of bits per transmission symbol on a burst-by-burst basis, in harmony with channel quality fluctuations. This is demonstrated in the paper for target bit error rates of 1 and 0.01%, respectively, in comparison to conventional fixed modems. However, the achievable gains depend strongly on the prevalent interference levels and hence interference cancellation is invoked on the basis of adjusting the demodulation decision boundaries after estimating the interfering channel’s magnitude and phase. Using the modem-mode switching levels of Table X and with the aid of interference cancellation, target BERs of 1 and 0.01% can be maintained over slow-fading channels for a wide range of channel Signal-to-noise ratios (SNR) and Signal-to-interference ratios (SIR), as seen in Figs. 20 and 21, respectively. Index Terms—Burst-by-burst adaptive modulation (modems), cochannel interference, interference cancellation

An M-QAM Signal Modulation Recognition Algorithm in AWGN Channel

Computing the distinct features from input data, before the classification, is a part of complexity to the methods of Automatic Modulation Classification (AMC) which deals with modulation classification was a pattern recognition problem. Although the algorithms that focus on MultiLevel Quadrature Amplitude Modulation (M-QAM) which underneath different channel scenarios was well detailed. A search of the literature revealed indicates that few studies were done on the classification of high order M-QAM modulation schemes like128-QAM, 256-QAM, 512-QAM and1024-QAM. This work is focusing on the investigation of the powerful capability of the natural logarithmic properties and the possibility of extracting Higher-Order Cumulant's (HOC) features from input data received raw. The HOC signals were extracted under Additive White Gaussian Noise (AWGN) channel with four effective parameters which were defined to distinguished the types of modulation from the set; 4-QAM~1024-QAM. This approach makes the recognizer more intelligent and improves the success rate of classification. From simulation results, which was achieved under statistical models for noisy channels, manifest that recognized algorithm executes was recognizing in M-QAM, furthermore, most results were promising and showed that the logarithmic classifier works well over both AWGN and different fading channels, as well as it can achieve a reliable recognition rate even at a lower signal-to-noise ratio (less than zero), it can be considered as an Integrated Automatic Modulation Classification (AMC) system in order to identify high order of M-QAM signals that applied a unique logarithmic classifier, to represents higher versatility, hence it has a superior performance via all previous works in automatic modulation identification systemComment: 18 page

Precoding for Outage Probability Minimization on Block Fading Channels

The outage probability limit is a fundamental and achievable lower bound on the word error rate of coded communication systems affected by fading. This limit is mainly determined by two parameters: the diversity order and the coding gain. With linear precoding, full diversity on a block fading channel can be achieved without error-correcting code. However, the effect of precoding on the coding gain is not well known, mainly due to the complicated expression of the outage probability. Using a geometric approach, this paper establishes simple upper bounds on the outage probability, the minimization of which yields to precoding matrices that achieve very good performance. For discrete alphabets, it is shown that the combination of constellation expansion and precoding is sufficient to closely approach the minimum possible outage achieved by an i.i.d. Gaussian input distribution, thus essentially maximizing the coding gain.Comment: Submitted to Transactions on Information Theory on March 23, 201