On linear MMSE based turbo-equalization of nonlinear Volterra channels

International audienceThis article deals with Minimum Mean Square Error (MMSE) turbo equalization of nonlinear interference using a volterra series decomposition of the underlying nonlinear channel. Although it has been often argued that linear MMSE based equalization is unsuited for cancelling nonlinear interference, we show that this common belief is not true in a strict sense. By a proper derivation of the linear based MMSE soft equalizer, we are able to show that the underlying structure of the equalizer is equivalent to a Soft Interference Canceller (SIC) treating both the linear and nonlinear interference. Based on these results, approximations are provided for lowering the computational complexity. Links to previously proposed “nonlinear” SIC are emphasized showing that the previously proposed structures are nothing but approximations of a linear MMSE receiver applied to nonlinear ISI channels. Simulations show that significant improvements can be achieved by using the proposed exact and approximate MMSE based turbo-equalizers

Asymptotic Analysis and Design of Iterative Receivers for Non Linear ISI Channels

International audienceIn this paper, iterative receiver analysis and design for non linear satellite channels is investigated. To do so, an EXtrinsic Information Transfer (EXIT) chart-based optimization is applied using two major assumptions: the equalizer outputs follow a Gaussian Mixture distribution since we use non-binary modulations and partial interleavers are used between the Low Density Parity Check (LDPC) code and the mapper. Achievable rates, performance and thresholds of the optimized receiver are analysed. The objective in fine is to answer the question: Is it worth optimizing an iterative receiver for non linear satellite channels

Energy-efficient diversity combining for different access schemes in a multi-path dispersive channel

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e ComputadoresThe forthcoming generation of mobile communications, 5G, will settle a new standard for a larger bandwidth and better Quality of Service (QoS). With the exploding growth rate of user generated data, wireless standards must cope with this growth and at the same time be energy efficient to avoid depleting the batteries of wireless devices. Besides these issues, in a broadband wireless setting QoS can be severely affected from a multipath dispersive channel and therefore be energy demanding. Cross-layered architectures are a good choice to enhance the overall performance of a wireless system. Examples of cross-layered Physical (PHY) - Medium Access Control (MAC) architectures are type-II Diversity Combining (DC) Hybrid-ARQ (H-ARQ) and Multi-user Detection (MUD) schemes. Cross-layered type-II DC H-ARQ schemes reuse failed packet transmissions to enhance data reception on posterior retransmissions; MUD schemes reuse data information from previously collided packets on posterior retransmissions to enhance data reception. For a multipath dispersive channel, a PHY layer analytical model is proposed for Single-Carrier with Frequency Domain Equalization (SC-FDE) that supports DC H-ARQ and MUD. Based on this analytical model, three PHY-MAC protocols are proposed. A crosslayered Time Division Multiple Access (TDMA) scheme that uses DC H-ARQ is modeled and its performance is studied in this document; the performance analysis shows that the scheme performs better with DC and achieves a better energy efficiency at the cost of a higher delay. A novel cross-layered prefix-assisted Direct-Sequence Code Division Multiple Access (DS-CDMA) scheme is proposed and modeled in this document, it uses principles of DC and MUD. This protocol performs better by means of additional retransmissions, achieving better energy efficiency, at the cost of higher redundancy from a code spreading gain. Finally, a novel cross-layered protocol H-ARQ Network Division Multiple Access (H-NDMA) is proposed and modeled, where the combination of DC H-ARQ and MUD is used with the intent of maximizing the system capacity with a lower delay; system results show that the proposed scheme achieves better energy efficiency and a better performance at the cost of a higher number of retransmissions. A comparison of the three cross-layered protocols is made, using the PHY analytical model, under normalized conditions using the same amount of maximum redundancy. Results show that the H-NDMA protocol, in general, obtains the best results, achieving a good performance and a good energy efficiency for a high channel load and low Signal-to-Noise Ratio (SNR). TDMA with DC H-ARQ achieves the best energy efficiency, although presenting the worst delay. Prefix-assisted DS-CDMA in the other hand shows good delay results but presents the worst throughput and energy efficiency

High performance faster-than-nyquist signaling

AbstractIn a wireless broadband context, multi-path dispersive channels can severely affectdata communication of Mobile Terminals (MTs) uplink.Single Carrier withFrequency-Domain Equalization (SC-FDE) has been proposed to deal with highlydispersive channels for the uplink of broadband wireless systems. However, currentsystems rely on older assumptions of the Nyquist theorem and assume that a systemneeds a minimum bandwidth 2Wper MT. Faster-Than-Nyquist (FTN) assumesthat it is possible to employ a bandwidth as low as 0.802 of the original Nyquistbandwidth with minimum loss - despite this, the current literature has only proposedcomplex receivers for a simple characterization of the wireless channel. Furthermore,the uplink of SC-FDE can be severely affected by a deep-fade and or poor channelconditions; to cope with such difficulties Diversity Combining (DC) Hybrid ARQ(H-ARQ) is a viable technique, since it combines the several packet copies sent bya MT to create reliable packet symbols at the receiver.In this thesis we consider the use of FTN signaling for the uplink of broadbandwireless systems employing SC-FDE based on the Iterative Block with DecisionFeedback Equalization (IB-DFE) receiver with a simple scheduled access HybridAutomatic Repeat reQuest (H-ARQ) specially designed taking into account thecharacteristics of FTN signals. This approach achieves a better performance thanNyquist signaling by taking advantage of the additional bandwidth employed of aroot-raised cosine pulse for additional diversity.Alongside a Packet Error Rate (PER) analytical model, simulation results show that this receiver presents a better performance when compared with a regular system,with higher system throughputs and a lower Energy per Useful Packet (EPUP)

Maximum-Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding

Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory). Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE) algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations

Symbol by Symbol Soft-Input Soft-Output Multiuser Detection for Frequency Selective Mimo Channels

We introduce a symbol by symbol, soft-input soft-output (SISO) multiuser detector for frequency selective multiple-input multiple-output (MIMO) channels. The basic principle of this algorithm is to extract a posteriori probabilities (APPs) of all interfering symbols at each symbol interval and then feed these updated APPs as a priori probabilities (apPs) for joint APP extraction in the next symbol interval. Unlike nearoptimal block oriented sphere decoding (SD) and soft decision equalization (SDE), the computational complexity of this updating APP (UA) algorithm is linear in the number of symbols but the exponential computational load of optimal joint APP extraction makes the basic UA impractical. To decrease computations we replace the optimal joint APP extractor by a groupwise SISO multiuser detector with a soft sphere decoding core. The resulting reduced complexity updating APP (RCUA) equalizer is flexible in different situations and outperforms the traditional sub-optimal MMSE-DFE without increasing the computational costs substantially

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems