Multi-service systems: an enabler of flexible 5G air-interface

Multi-service system is an enabler to flexibly support diverse communication requirements for the next generation wireless communications. In such a system, multiple types of services co-exist in one baseband system with each service having its optimal frame structure and low out of band emission (OoBE) waveforms operating on the service frequency band to reduce the inter-service-band-interference (ISvcBI). In this article, a framework for multi-service system is established and the challenges and possible solutions are studied. The multi-service system implementation in both time and frequency domain is discussed. Two representative subband filtered multicarrier (SFMC) waveforms: filtered orthogonal frequency division multiplexing (F-OFDM) and universal filtered multi-carrier (UFMC) are considered in this article. Specifically, the design methodology, criteria, orthogonality conditions and prospective application scenarios in the context of 5G are discussed. We consider both single-rate (SR) and multi-rate (MR) signal processing methods. Compared with the SR system, the MR system has significantly reduced computational complexity at the expense of performance loss due to inter-subband-interference (ISubBI) in MR systems. The ISvcBI and ISubBI in MR systems are investigated with proposed low-complexity interference cancelation algorithms to enable the multi-service operation in low interference level conditions

Personal Sound Zones by Subband Filtering and Time Domain Optimization

[EN] Personal Sound Zones (PSZ) systems aim to render independent sound signals to multiple listeners within a room by using arrays of loudspeakers. One of the algorithms used to provide PSZ is Weighted Pressure Matching (wPM), which computes the filters required to render a desired response in the listening zones while reducing the acoustic energy arriving to the quiet zones. This algorithm can be formulated in time and frequency domains. In general, the time-domain formulation (wPM-TD) can obtain good performance with shorter filters and delays than the frequency-domain formulation (wPM-FD). However, wPM-TD requires higher computation for obtaining the optimal filters. In this article, we propose a novel approach to the wPM algorithm named Weighted Pressure Matching with Subband Decomposition (wPMSD), which formulates an independent time-domain optimization problem for each of the subbands of a Generalized Discrete Fourier Transform (GDFT) filter bank. Solving the optimization independently for each subband has two main advantages: 1) lower computational complexity than wPM-TD to compute the optimal filters; 2) higher versatility than the classic wPM algorithms, as it allows different configurations (sets of loudspeakers, filter lengths, etc.) in each subband. Moreover, filtering the input signals with a GDFT filter bank (as in wPM-SD) requires lower computational effort than broadband filtering (as in wPM-TD and wPM-FD), which is beneficial for practical PSZ systems. We present experimental evaluations showing that wPM-SD offers very similar performance to wPM-TD. In addition, two cases where the versatility of wPM-SD is beneficial for a PSZ system are presented and experimentally validated.This work was supported by Grants RTI2018-098085-B-C41 (MCIU/AEI/FEDER, UE), RED2018-102668-T and PROMETEO/2019/109. The work of Vicent Moles-Cases has been supported by Spanish Ministry of Education under Grant FPU17/01288.Molés-Cases, V.; Piñero, G.; Diego Antón, MD.; Gonzalez, A. (2020). Personal Sound Zones by Subband Filtering and Time Domain Optimization. IEEE/ACM Transactions on Audio Speech and Language Processing. 28:2684-2696. https://doi.org/10.1109/TASLP.2020.3023628S268426962

Orthonormal and biorthonormal filter banks as convolvers, and convolutional coding gain

Convolution theorems for filter bank transformers are introduced. Both uniform and nonuniform decimation ratios are considered, and orthonormal as well as biorthonormal cases are addressed. All the theorems are such that the original convolution reduces to a sum of shorter, decoupled convolutions in the subbands. That is, there is no need to have cross convolution between subbands. For the orthonormal case, expressions for optimal bit allocation and the optimized coding gain are derived. The contribution to coding gain comes partly from the nonuniformity of the signal spectrum and partly from nonuniformity of the filter spectrum. With one of the convolved sequences taken to be the unit pulse function,,e coding gain expressions reduce to those for traditional subband and transform coding. The filter-bank convolver has about the same computational complexity as a traditional convolver, if the analysis bank has small complexity compared to the convolution itself

Filtered OFDM systems, algorithms and performance analysis for 5G and beyond

Filtered orthogonal frequency division multiplexing (F-OFDM) system is a promising waveform for 5G and beyond to enable multi-service system and spectrum efficient network slicing. However, the performance for F-OFDM systems has not been systematically analyzed in literature. In this paper, we first establish a mathematical model for F-OFDM system and derive the conditions to achieve the interference-free one-tap channel equalization. In the practical cases (e.g., insufficient guard interval, asynchronous transmission, etc.), the analytical expressions for inter-symbol-interference (ISI), inter-carrier-interference (ICI) and adjacent-carrier-interference (ACI) are derived, where the last term is considered as one of the key factors for asynchronous transmissions. Based on the framework, an optimal power compensation matrix is derived to make all of the subcarriers having the same ergodic performance. Another key contribution of the paper is that we propose a multi-rate F-OFDM system to enable low complexity low cost communication scenarios such as narrow band Internet of Things (IoT), at the cost of generating inter-subband-interference (ISubBI). Low computational complexity algorithms are proposed to cancel the ISubBI. The result shows that the derived analytical expressions match the simulation results, and the proposed ISubBI cancelation algorithms can significantly save the original F-OFDM complexity (up to 100 times) without significant performance los

Efficient Fast-Convolution-Based Waveform Processing for 5G Physical Layer

This paper investigates the application of fast-convolution (FC) filtering schemes for flexible and effective waveform generation and processing in the fifth generation (5G) systems. FC-based filtering is presented as a generic multimode waveform processing engine while, following the progress of 5G new radio standardization in the Third-Generation Partnership Project, the main focus is on efficient generation and processing of subband-filtered cyclic prefix orthogonal frequency-division multiplexing (CP-OFDM) signals. First, a matrix model for analyzing FC filter processing responses is presented and used for designing optimized multiplexing of filtered groups of CP-OFDM physical resource blocks (PRBs) in a spectrally well-localized manner, i.e., with narrow guardbands. Subband filtering is able to suppress interference leakage between adjacent subbands, thus supporting independent waveform parametrization and different numerologies for different groups of PRBs, as well as asynchronous multiuser operation in uplink. These are central ingredients in the 5G waveform developments, particularly at sub-6-GHz bands. The FC filter optimization criterion is passband error vector magnitude minimization subject to a given subband band-limitation constraint. Optimized designs with different guardband widths, PRB group sizes, and essential design parameters are compared in terms of interference levels and implementation complexity. Finally, extensive coded 5G radio link simulation results are presented to compare the proposed approach with other subband-filtered CP-OFDM schemes and time-domain windowing methods, considering cases with different numerologies or asynchronous transmissions in adjacent subbands. Also the feasibility of using independent transmitter and receiver processing for CP-OFDM spectrum control is demonstrated

On the optimality of subband adaptive filters

In this paper, we derive a polyphase analysis to determine the optimum filters in a subband adaptive filter (SAF) system. The structure of this optimum solution deviates from the standard SAF approach and presents its best possible solution only as an approximation. Besides this new insight into SAF error sources, the discussed analysis allows to calculate the optimum subband responses and the standard SAF approximation. Examples demonstrating the validity of our analysis and its use for determining SAF errors are presented

Filterbank optimization with convex objectives and the optimality of principal component forms

This paper proposes a general framework for the optimization of orthonormal filterbanks (FBs) for given input statistics. This includes as special cases, many previous results on FB optimization for compression. It also solves problems that have not been considered thus far. FB optimization for coding gain maximization (for compression applications) has been well studied before. The optimum FB has been known to satisfy the principal component property, i.e., it minimizes the mean-square error caused by reconstruction after dropping the P weakest (lowest variance) subbands for any P. We point out a much stronger connection between this property and the optimality of the FB. The main result is that a principal component FB (PCFB) is optimum whenever the minimization objective is a concave function of the subband variances produced by the FB. This result has its grounding in majorization and convex function theory and, in particular, explains the optimality of PCFBs for compression. We use the result to show various other optimality properties of PCFBs, especially for noise-suppression applications. Suppose the FB input is a signal corrupted by additive white noise, the desired output is the pure signal, and the subbands of the FB are processed to minimize the output noise. If each subband processor is a zeroth-order Wiener filter for its input, we can show that the expected mean square value of the output noise is a concave function of the subband signal variances. Hence, a PCFB is optimum in the sense of minimizing this mean square error. The above-mentioned concavity of the error and, hence, PCFB optimality, continues to hold even with certain other subband processors such as subband hard thresholds and constant multipliers, although these are not of serious practical interest. We prove that certain extensions of this PCFB optimality result to cases where the input noise is colored, and the FB optimization is over a larger class that includes biorthogonal FBs. We also show that PCFBs do not exist for the classes of DFT and cosine-modulated FBs