Time Reversal with Post-Equalization for OFDM without CP in Massive MIMO

This paper studies the possibility of eliminating the redundant cyclic prefix (CP) of orthogonal frequency division multiplexing (OFDM) in massive multiple-input multiple-output systems. The absence of CP increases the bandwidth efficiency in expense of intersymbol interference (ISI) and intercarrier interference (ICI). It is known that in massive MIMO, different types of interference fade away as the number of base station (BS) antennas tends to infinity. In this paper, we investigate if the channel distortions in the absence of CP are averaged out in the large antenna regime. To this end, we analytically study the performance of the conventional maximum ratio combining (MRC) and realize that there always remains some residual interference leading to saturation of signal to interference (SIR). This saturation of SIR is quantified through mathematical equations. Moreover, to resolve the saturation problem, we propose a technique based on time-reversal MRC with zero forcing multiuser detection (TR-ZF). Thus, the SIR of our proposed TR-ZF does not saturate and is a linear function of the number of BS antennas. We also show that TR-ZF only needs one OFDM demodulator per user irrespective of the number of BS antennas; reducing the BS signal processing complexity significantly. Finally, we corroborate our claims as well as analytical results through simulations.Comment: 7 pages, 3 figure

Delay Alignment Modulation: Manipulating Channel Delay Spread for Efficient Single- and Multi-Carrier Communication

The evolution of mobile communication networks has always been accompanied by the advancement of ISI mitigation techniques, from equalization in 2G, spread spectrum and RAKE receiver in 3G, to OFDM in 4G and 5G. Looking forward towards 6G, by exploiting the high spatial resolution brought by large antenna arrays and the multi-path sparsity of mmWave and Terahertz channels, a novel ISI mitigation technique termed delay alignment modulation (DAM) was recently proposed. However, existing works only consider the single-carrier perfect DAM, which is feasible only when the number of BS antennas is no smaller than that of channel paths, so that all multi-path signal components arrive at the receiver simultaneously and constructively. This imposes stringent requirements on the number of BS antennas and multi-path sparsity. In this paper, we propose a generic DAM technique to manipulate the channel delay spread via spatial-delay processing, thus providing a flexible framework to combat channel time dispersion for efficient single- or multi-carrier transmissions. We first show that when the number of BS antennas is much larger than that of channel paths, perfect delay alignment can be achieved to transform the time-dispersive channel to time non-dispersive channel with the simple delay pre-compensation and path-based MRT beamforming. When perfect DAM is infeasible or undesirable, the proposed generic DAM technique can be applied to significantly reduce the channel delay spread. We further propose the novel DAM-OFDM technique, which is able to save the CP overhead or mitigate the PAPR issue suffered by conventional OFDM. We show that the proposed DAM-OFDM involves joint frequency- and time-domain beamforming optimization, for which a closed-form solution is derived. Simulation results show that the proposed DAM-OFDM outperforms the conventional OFDM in terms of spectral efficiency, BER and PAPR.Comment: 16 Pages, 15 figure

Experimental Analysis of Wideband Spectrum Sensing Networks Using Massive MIMO Testbed

In this paper, we investigate the practical implication of employing virtual massive multiple-input-multiple output (MIMO) based distributed decision fusion (DF) for collaborative wideband spectrum sensing (WSS) in a cognitive radio (CR)-like network. Towards that end, an indoor-only measurement campaign has been conducted to capture the propagation statistics of a 4 × 64 massive MIMO system with one authorized primary user (PU) and 4 unauthorized secondary users (SUs) transmitting simultaneously over a 20 MHz band divided into 1200 subcarriers. The frequency subcarriers belong to an Orthogonal-frequency-division-multiplexing (OFDM)-like set-up without the addition of cyclic prefix (CP) to the transmit symbols. Measurements are accumulated for different relative positions of the SUs which are analysed to extract fading, shadowing, noise and interference power statistics. Log-likelihood ratio (LLR) based fusion rule and three different sets of sub-optimum fusion rules along with their time-reversed versions are formulated for combining decisions on the availability of each subcarrier transmitted by the SUs. The extracted channel characteristics are incorporated in both analytical and simulated performance analysis of the devised fusion rules for comparison and testing the validity of distributed DF in realistic collaborative WSS scenario

Joint precoding and antenna selection in massive mimo systems

This thesis presents an overview of massive multiple-input multiple-output (MIMO) systems and proposes new algorithms to jointly precode and select the antennas. Massive MIMO is a new technology, which is candidate for comprising the fifth-generation (5G) of mobile cellular systems. This technology employs a huge amount of antennas at the base station and can reach high data rates under favorable, or asymptotically favorable, propagation conditions, while using simple linear processing. However, massive MIMO systems have some drawbacks, such as the high cost related to the base stations. A way to deal with this issue is to employ antenna selection algorithms at the base stations. These algorithms reduce the number of active antennas, decreasing the deployment and maintenance costs related to the base stations. Moreover, this thesis also describes a class of nonlinear precoders that are rarely addressed in the literature; these techniques are able to generate precoded sparse signals in order to achieve joint precoding and antenna selection. This thesis proposes two precoders belonging to this class, where the number of selected antennas is controlled by a design parameter. Simulation results show that the proposed precoders reach a lower bit-error rate than the classical antenna selection algorithms. Furthermore, simulation results show that the proposed precoders present a linear relation between the aforementioned design parameter that controls the signals’ sparsity and the number of selected antennas. Such relation is invariant to the number of base station’s antennas and the number of terminals served by this base station.Esta dissertação apresenta uma visão geral sobre MIMO (do termo em inglês, multiple-input multiple-output) massivo e propõe novos algoritmos que permitem a pré-codificacão de sinais e a seleção de antenas de forma simultânea. MIMO massivo é uma nova tecnologia candidata para compor a quinta geração (5G) dos sistemas celulares. Essa tecnologia utiliza uma quantidade muito grande de antenas na estação-base e, sob condições de propagação favorável ou assintoticamente favorável, pode alcançar taxas de transmissão elevadas, ainda que utilizando um simples processamento linear. Entretanto, os sistemas MIMO massivo apresentam algumas desvantagens, como por exemplo, o alto custo de implementação das estações-bases. Uma maneira de lidar com esse problema é utilizar algoritmos de seleção de antenas na estação-base. Com esses algoritmos é possível reduzir o número de antenas ativas e consequentemente reduzir o custo nas estações-bases. Essa dissertação também apresenta uma classe pouco estudada de pré-codificadores não-lineares que buscam sinais pré-codificados esparsos para realizar a seleção de antenas conjuntamente com a pré-codificação. Além disso, este trabalho propõem dois novos pré-codificadores pertencentes a essa classe, para os quais o número de antenas selecionadas é controlado por um parâmetro de projeto. Resultados de simulações mostram que os pré-codificadores propostos conseguem uma BER (do termo em inglês, bit-error rate) menor que os algoritmos clássicos usados para selecionar antenas. Além disso, resultados de simulações mostram que os pré-codificadores propostos apresentam uma relação linear com o parâmetro de projeto que controla a quantidade de antenas selecionadas; tal relação independe do número de antenas na estação-base e do número de terminais servidos por essa estação

OFDM Without CP in Massive MIMO

We study the possibility of removing the cyclic prefix (CP) overhead from orthogonal frequency division multiplexing (OFDM) in massive multiple-input multiple-output (MIMO) systems. We consider the uplink transmission, while our results are applicable to the downlink as well. The absence of CP increases the spectral efficiency in expense of intersymbol interference and intercarrier interference. It is known that in massive MIMO, the effects of uncorrelated noise and multiuser interference vanish as the number of base station antennas tends to infinity. To investigate if the channel distortions in the absence of CP fade away, we study the performance of the standard maximum ratio combining receiver. Our analysis reveals that in this receiver, there always remains some residual interference leading to saturation of signal-to-interference-plus-noise ratio. To resolve this problem, we propose using the time reversal (TR) technique. Moreover, in order to further reduce the multiuser interference, we propose a zero-forcing equalization to be deployed after the TR combining. We compare the achievable rate of the proposed system with that of the conventional CP-OFDM. We show that in realistic channels, a higher spectral efficiency is achieved by removing the CP from OFDM, while reducing the computational complexity