Joint detection and channel estimation for MIMO systems with SC-FDE modulations

SC modulation (Single-Carrier) with FDE (Frequency-Domain Equalization) allows excellent performance in severely time-dispersive channels, provided that accurate channel estimates are available at the receiver. For this purpose, pilot symbols and/or training sequences are usually multiplexed with data symbols, which lead to spectral degradation. As an alternative, we can use implicit pilots (i.e., pilots superimposed to data). In this paper we consider MIMO SC-FDE systems where the channel estimation is based on either explicit or implicit pilots, for comparison purposes. An iterative receiver with joint equalization, turbo decoding and channel estimation was employed for optimum results, and to reduce the high interference levels between data and pilots (for the implicit pilots). The main differences between the different schemes are discussed and the performance results show that the use of the proposed techniques for channel estimation yield excellent results.info:eu-repo/semantics/acceptedVersio

Superimposed training for single carrier transmission in future mobile communications

The amount of wireless devices and wireless traffic has been increasing exponentially for the last ten years. It is forecasted that the exponential growth will continue without saturation till 2020 and probably further. So far, network vendors and operators have tackled the problem by introducing new evolutions of cellular macro networks, where each evolution has increased the physical layer spectral efficiency. Unfortunately, the spectral efficiency of the physical layer is achieving the Shannon-Hartley limit and does not provide much room for improvement anymore. However, considering the overhead due to synchronization and channel estimation reference symbols in the context of physical layer spectral efficiency, we believe that there is room for improvement. In this thesis, we will study the potentiality of superimposed training methods, especially data-dependent superimposed training, to boost the spectral efficiency of wideband single carrier communications even further. The main idea is that with superimposed training we can transmit more data symbols in the same time duration as compared to traditional time domain multiplexed training. In theory, more data symbols means more data bits which indicates higher throughput for the end user. In practice, nothing is free. With superimposed training we encounter self-interference between the training signal and the data signal. Therefore, we have to look for iterative receiver structures to separate these two or to estimate both, the desired data signal and the interfering component. In this thesis, we initiate the studies to find out if we truly can improve the existing systems by introducing the superimposed training scheme. We show that in certain scenarios we can achieve higher spectral efficiency, which maps directly to higher user throughput, but with the cost of higher signal processing burden in the receiver. In addition, we provide analytical tools for estimating the symbol or bit error ratio in the receiver with a given parametrization. The discussion leads us to the conclusion that there still remains several open topics for further study when looking for new ways of optimizing the overhead of reference symbols in wireless communications. Superimposed training with data-dependent components may prove to provide extra throughput gain. Furthermore, the superimposed component may be used for, e.g., improved synchronization, low bit-rate signaling or continuous tracking of neighbor cells. We believe that the current systems could be improved by using the superimposed training collectively with time domain multiplexed training

Partial-Data Superimposed Training with Data Precoding for OFDM Systems

Superimposed training (ST) is a recently addressed technique used for channel estimation where known training sequences are arithmetically added to data symbols, avoiding the use of dedicated pilot subcarriers, and thus, increasing the available bandwidth compared with traditional pilot symbol assisted modulation schemes. However, the system handles data interference over channel estimation as a result of the ST process; also, data detection is degraded by pilot interference. Recent ST methods have analyzed the data interference and presented schemes that deal with it. We propose a novel superimposed model over a precoded data scheme, named partial-data superimposed training (PDST), where an interference control factor assigns the adequate information level to be added to the training sequence in orthogonal frequency division multiplexing systems. Also, a data detection method is introduced to improve the symbol error rate performance. Moreover, a capacity analysis of the system has been derived. Finally, simulation results confirm that performance of PDST is superior to previous proposals

Optical Space Division Multiplexing in Short Reach Multi-Mode Fiber Systems

The application of space division multiplexing to fiber-optic communications is a promising approach to further increase the channel capacity of optical waveguides. In this work, short reach and low-cost optical space division multiplexing systems with intensity modulation and direct detection (IM/DD) are in the focus of interest. Herein, different modes are utilized to generate spatial diversity in a multi-mode fiber. In such IM/DD systems, the process of square-law detection is inherently non-linear. In order to obtain an understanding of the channel characteristics, a system model is developed, which is able to show under which conditions the system can be considered linear in baseband. It is shown that linearity applies in scenarios with low mode cross-talk. This enables the use of linear multiple-input multiple-output (MIMO) signal processing strategies for equalization purposes. In conditions with high mode cross-talk, significant interference occurs, and the transmitted information cannot be extracted at the receiver. Furthermore, a method to determine the power coupling coefficients between mode groups is presented that does not require the excitation of individual modes, and hence it can be realized with inexpensive components. In addition, different optical components are analyzed with respect for their suitability in MIMO setups with IM/DD. The conventional approach with single-mode fiber to multi-mode fiber offset launches and optical couplers as well as a configuration that utilizes multi-segment detection are feasible options for a (2x2) setup. It is further shown that conventional photonic lanterns are not suited for MIMO with IM/DD due to their low mode orthogonality during the multiplexing process. In order to enable higher order MIMO configurations, devices for mode multiplexing and demultiplexing need to be developed, which exhibit a high mode orthogonality on one hand and are low-cost on the other hand

MIMO-OFDM channel estimation: a pilot sequence design for time-domain processing

A pilot sequence design for MIMO-OFDM systems is investigated where all transmit antennas share the same sub-carriers to convey pilot symbols. The pilot sequences are endowed with phase-shifting properties, granting the receiver the possibility of extracting the impulse responses for all channels directly from the antennas’ time-domain received signals, without co-channel interference. A linear processing of the timedomain samples is all that is needed to get the channel impulse responses, resulting in an algorithm with very low computational load. The feasibility of the investigated method is substantiated by system simulation using indoor and outdoor broadband wireless channel models

Optimum Averaging of Superimposed Training Schemes in OFDM under Realistic Time-Variant Channels

The current global bandwidth shortage in orthogonal frequency division multiplexing (OFDM)-based systems motivates the use of more spectrally efficient techniques. Superimposed training (ST) is a candidate in this regard because it exhibits no information rate loss. Additionally, it is very flexible to deploy and it requires low computational cost. However, data symbols sent together with training sequences cause an intrinsic interference. Previous studies, based on an oversimplified channel (a quasi-static channel model) have solved this interference by averaging the received signal over the coherence time. In this paper, the mean square error (MSE) of the channel estimation is minimized in a realistic time-variant scenario. The optimization problem is stated and theoretical derivations are presented to attain the optimum amount of OFDM symbols to be averaged. The derived optimal value for averaging is dependent on the signal-to-noise ratio (SNR) and it provides a better MSE, of up to two orders of magnitude, than the amount given by the coherence time. Moreover, in most cases, the optimal number of OFDM symbols for averaging is much shorter, about 90% reduction of the coherence time, thus it provides a decrease of the system delay. Therefore, these results match the goal of improving performance in terms of channel estimation error while getting even better energy efficiency, and reducing delays.This work was supported by the Spanish National Project Hybrid Terrestrial/Satellite Air Interface for 5G and Beyond - Areas of Dif-cult Access (TERESA-ADA) [Ministerio de Economía y Competitividad (MINECO)/Agencia Estatal de Investigación (AEI)/Fondo Europeo de Desarrollo Regional (FEDER), Unión Europea (UE)] under Grant TEC2017-90093-C3-2-R

A Study on MIMO Wireless Communication Channel Performance in Correlated Channels

MIMO wireless communication system is gaining popularity by days due to its versatility and wide applicability. When signal travels through wireless link it gets affected due to the disturbances present in the channel i.e. different sorts of interference and noise. Plus because there may or may not be a Line of sight (LOS) path between transmitter and receiver signal copies leaving the transmitter at the same time reaches the receiver with different delays and attenuation due to multiple reflections and interfere with each other at the receiver. Therefore fading of received signal power is also observed in case of a wireless MIMO link. In case of wireless two most important objectives can be channel estimation and signal detection. The importance of the wireless channel estimation can be attributed to faithful signal detection and transmit beam forming, power allocation etc. when Channel state information (CSI) is communicated to the transmitter via feedback loop in case of uni-directional channel or by simultaneous estimation by the transmitter itself in case of bi-directional channel. This text introduces some aspects of signal detection and mostly different aspects of channel estimation and explains why it is important in context of signal detection, beam forming etc. A brief introduction to antenna arrays and beam forming procedures have been given here. The cause of occurrence of spatial and temporal correlations have been discussed and different ways of modelling the spatial and temporal correlations involved are also briefly introduced in this text. How different link and link-end properties e.g. antenna spacing, angular spread of radiation beam, mean angle of radiation, mutual coupling present between elements of an antenna array etc. affects the channel correlations thereby affecting the performance of the MIMO wireless communication channel. Modelling of antenna mutual coupling and different estimation and compensation techniques are also discussed here