Spatial Modulation for Multiple-Antenna Communication

Auteurs : Marco di Renzo
Publication REE REE 2018-2


Spatial Modulation for Multiple-Antenna Communication


417.61 Ko


Creative Commons Aucune (Tous droits réservés)
<resource  xmlns:xsi=""
        <identifier identifierType="DOI">10.23723/1301:2018-2/22862</identifier><creators><creator><creatorName>Marco di Renzo</creatorName></creator></creators><titles>
            <title>Spatial Modulation for Multiple-Antenna Communication</title></titles>
        <resourceType resourceTypeGeneral="Text">Text</resourceType><dates>
	    <date dateType="Created">Sat 12 May 2018</date>
	    <date dateType="Updated">Sat 12 May 2018</date>
            <date dateType="Submitted">Sun 20 May 2018</date>
	    <alternateIdentifier alternateIdentifierType="bitstream">831ce71c06ee681f6f62d074309b177c4aafc354</alternateIdentifier>
            <description descriptionType="Abstract"></description>

10 Z REE N°2/2018 LES GRANDS PRIX 2017 DE LA SEE LES GRANDS PRIX 2017 DE LA SEE Introduction The Internet of Things (IoT) can be broadly defined as the current com bro y defined a (IoT) can be b - mercial effort for integrating a wide variety of technical and commercial de variety of technica co g a wide information-generating components to provide new business opportunities provide e new busi oppo ompon based upon device and system intelligence. Several potential application ce. Se Several p ial app system intelligence. areas have been identified for the IoT, which include smart homes, wea nclude t homes or the IoT, which in - rables, smart cities, the smart grid, the industrial Internet, connected cars, al Interne connecte , the industria d, connected health, smart retail, smart supply chain, and smart farming. and sm mart farming art supply In the context of IoT-based applications, the so-called connected objects lled c connected cations, the so-calle are expected to require more modest data rates, lower power consumption, ower consu n, data rates, lower pow and smaller form factors compared with those of typical mobile multimed mob obile m edia hose of typical m services. By contrast, they are expected to support higher data rates her da es at a pport high ed t higher power consumption, and at a more bulky form factor compar tor compared with ore bulky typical wireless sensor nodes. Hence, new air interface technique chniqu ues have to ew air interface t be developed, which are able to satisfy these new emerging requirements ng re requirements hese new emerging and to offer a better Spectral Efficiency (SE) vs. Energy Efficiency (EE) design y y (EE) desig s. Energy Efficiency SE flexibility. In this context, Multiple-Input-Multiple-Output (MIMO) techniques MO) t ) techniq Output (MIMO Multip [1] are expected to provide the necessary design flexibility to meet thes y to m these b l ary design fl requirements. Why for emerging IoT applications is a O paradigm a new MIMO ons i necessary? The capacity of MIMO systems is proportional to the minimum of the num inimum portional to p - ber of transmit and receive antennas. This implies that the throughput may t the th ut may his implies th nnas be increased linearly with the number of antennas. As a consequence, MIMO a conse equence, MIMO antennas. As a mber techniques can provide high data rates without any bandwidth expansion and dwi dwidth expansion an out any band ta rates hi without increasing the transmit power [2]. However, in practice, conventional w n practice, convent owever, in p power [2 he tra MO systems rely on a multiplicity of independent circuits for each available dent cir MIMO ircuits for each dent c licity of ind ely on a nna element, such as power amplifiers, RF front-ends, mixers, synthesi s, RF front antenn d er amplifier nt, such - ers, etc., which substantially increase the circuit power dissipation of all e the circ zers, filte e the circuit power dissipation ally increase c., which s elements. It is known, in particular, that the power amplifiers dissipate pa network e ar, that the power amplifiers d particular, ments. It is k ority of the power consumed in current cellular base stations [3]. wer consumed in c the major current cellular base statio of the powe Recent studies, in fact, have proved that the EE gain of MIMO transmis Recent studies, in fact, have pro Re Rece hat the EE gai s, in fact, have es in - ncreases with the number of antennas, provided that only the transmit ncreases wi sion in with the number of antenn wer is taken into account and that their circuit power dissipation is neglec powe to account and that their circuit p - ted. On the other hand, the EE gain of MIMO transmission remains modest he EE gain of MIM Le Prix Brillouin-Glavieux est décerné conjointem intem jointem décerné ment par l’IEEE et la SEE. Il a pour but de promou our but a SEE. Il a t de promou- voir l’interaction entre recherche n entre l’interactio fondamentale, enseignement , ense damentale, ement supérieur et industri ndus rieur et ind su dustrie de contribuer ainsi au triangle ribue contribu et de uer ainsi au triang a connaissance : sciences, naissa de la c sance : sciences, ogie et innovation gie et technolog ovation. Marco Di Renzo Prix Brillouin-Glavieux Chargé de Recherche CNRS erche Laboratoire des Signaux et Systèmes gnaux èmes (L2 L2S) Université Paris-Saclay (CN ris-Sacla NRS – CentraleSupél lec, U v niv U U . Paris ris- is-Sud) v v M D R Spatial Modulation for Multiple-Antenna Communication %TTPMGEXMSRXSXLI-RXIVRIX SJ8LMRKW -S8
*VSQ8LISV] K XS4VEGXMG XS4 XMGI Spatial Modulation for Multiple-Antenna Communication and decreases with the number of active transmit antennas, if realistic power consumption models are considered [3]. These results highlight that the design of energy efficient and low-complexity MIMO transmission schemes is an open research issue, especially in the context of IoT applications. In this context, the design of MIMO transmission schemes that exploit fewer RF chains compared to the number of avai- lable radiating elements is currently emerging as a promising research field [2]. Usually, this family of MIMO designs is refer- red to as single-RF MIMO. Suffice to say, however, that various compromise-schemes exist, where a subset of the antennas is activated, which determines the number of RF-chains that is needed. Hence, in parlance, we can refer to these schemes as single-RF, full-RF and few-RF arrangements. Why having fewer RF chains than radiating elements is beneficial for designing spectral- and energy-efficient MIMO schemes? The fundamental idea behind the few-RF MIMO concept is to attain spatial multiplexing and/or transmit-diversity gains with the aid of many antenna-elements, where only a subset of them – or possibly just a single antenna-element – is activa- ted at the transmitter at any modulation instant. The rationale behind the full-RF to few-RF paradigm shift in MIMO design originates from the consideration that multiple transmit anten- nas (radiating elements) may be accommodated at both the transmitters and receivers, bearing in mind that the complexity and power consumption/dissipation of MIMO transmission is mainly determined by the number of simultaneously active transmit antennas, i.e., by the number of RF chains [2]. Fueled by these considerations, Spatial Modulation (SM) has recently established itself as a promising transmission concept, which belongs to the few-RF MIMO wireless system family, whilst exploiting the availability of multiple antennas in a novel fashion compared to state-of-the-art high-complexi- ty and power-hungry classic MIMO systems [2]. In simple terms, SM can be regarded as a MIMO concept that pos- sesses a larger set of radiating elements than the number of transmit-electronics chains. SM-MIMO takes advantage of the entire antenna-array at the transmitter, whilst using a limited number of RF chains. The main distinguishing feature of SM- MIMO is that it maps additional information bits onto a “SM constellation diagram”, where each constellation element is formed either by a single antenna-element or a subset of antenna-elements. These unique characteristics result in high-rate MIMO implementations relying on a reduced signal processing and circuit complexity, as well as an improved EE. Recent analytical and simulation studies have shown that SM-MIMO has the inherent potential of outperforming many state-of-the-art MIMO schemes under the fair assumption that the number of RF chains is the same [4]-[6]. Readers interested in further information on SM-MIMO systems are invited to consult recently published and comprehensive sur- vey papers [7]-[11]. It is worth mentioning that the SM-MIMO concept is one of the proposed technologies for next-genera- tion communication systems [12]. Spatial Modulation We introduce the SM-MIMO concept with the aid of a simple example. We denote by Nt and Nr the number of Transmit Antennas (TAs) and Receive Antennas (RAs), res- pectively. The cardinality of the signal-constellation diagram is denoted by M. In general, Nt, Nr and M can be chosen independently of each other. If a Maximum-Likelihood (ML-) optimum demodulation is considered at the receiver, Nr can be chosen independently of Nt [7]. For ease of illustration, a single RF chain is assumed to be available at the transmitter (single-RF MIMO). In figure 1, the SM-MIMO concept is illustrated for Nt = M = 2 and is compared to Spatial Multiplexing (SMX) and REE N°2/2018 Z 11 Figure 1: SM-MIMO compared with SMX and OSTBC. 12 ZREE N°2/2018 LES GRANDS PRIX 2017 DE LA SEE Orthogonal Space-Time Block Code (OSTBC) schemes. In the latter case, the Alamouti scheme is considered [7]. Com- pared with SMX and OSTBC, we observe that only one (S1) out of the two symbols is explicitly transmitted in SM-MIMO, while the other symbol (S2) is implicitly transmitted by deter- mining the index of the active TA in each channel use. In SM-MIMO, in other words, the information symbols are mo- dulated onto two information carrying units: 1) a modulated symbol and 2) a single active TA via an information-driven antenna-switching mechanism. In Figure 2 and Figure 3, the encoding principle of SM- MIMO is illustrated for Nt = M = 4 by considering two generic channel uses, and the concept of “SM or spatial-constellation diagram” is introduced. The illustrations shown in Figure 2 and Figure 3 highlight some unique characteristics of SM-MIMO: s 4HEACTIVATED4!MAYCHANGEEVERYCHANNELUSEACCORDING to the input information bits. Thus, TA switching is an effec- tive way of mapping the information bits to TA indices and of increasing the transmission rate. Figure 2: Illustration of the encoding principle of SM-MIMO (channel use 1). Figure 3: Illustration of the encoding principle of SM-MIMO (channel use 2). REE N°2/2018 Z 13 Spatial Modulation for Multiple-Antenna Communication s 4HE INFORMATION BITS ARE MODULATED ONTO A THREE
DIMEN- sional constellation diagram, which generalizes the known two-dimensional (complex-valued) signal-constellation dia- gram of conventional modulation schemes. s 4HETHIRDDIMENSIONISPROVIDEDBYTHEANTENNA
ARRAY WHERE some of the bits are mapped to the TAs. In SM-MIMO re- search, this third dimension is often termed as the “spatial- constellation diagram” [2]. Spatial Modulation Based on Reconfigu- rable Antennas (RectAnt-SM) Reconfigurability can be thought of as a software-defi- ned functionality, where flexibility is controlled predomina- tely through the specification of bit patterns. Reconfigurable systems can be as simple as a single switch, or as abstract and powerful as programmable matter. One of the most pre- valent pursuits in reconfigurable RF research has been in the development of antennas, which have been studied extensi- vely. For the most part, a Reconfigurable Antenna (RectAnt) is a set of passive structures infused with switches, which are opened and closed to elicit desired resonances for end- user applications. In the burgeoning IoT market, RectAnts are expected to provide the opportunity for better designing communication systems that fulfill important conflicting trade-offs, such as reducing the size, power consumption, and cost of the IoT devices, while simultaneously increasing their data rate through innovative MIMO technologies [13]. The idea of using reconfigurable antennas for implemen- ting and generalizing the SM principle was introduced by the author in [7] with the twofold attempt of increasing the achievable data rate and reducing the implementation com- plexity, e.g., by avoiding the need of using mechanical or RF switches. In general terms, reconfiguring an antenna is achie- ved through deliberately changing its radiation characteristics, e.g., its far field radiation pattern. In practice, this change is obtained in a controlled manner, by adequately redistributing the antenna currents and, thus, altering the electromagne- tic fields of the antenna’s effective aperture. In other words, thus, the far field antenna radiation pattern can be modified by appropriately controlling the distribution of the current of the antennas. In Figure 4, the concept of RectAnt-SM is illustrated with a simple example. Let us assume that the transmitter is equip- ped with a RectAnt that is capable of producing the far field radiation patterns depicted in Figure 4. The operating prin- ciple of RectAnt-SM is similar to that of SM-MIMO, which is illustrated in Figure 2 and Figure 3, with the only difference that part of the information bits that is transmitted is not en- coded into the TA but into the activated radiation pattern, by appropriately modifying the distribution of the current inside the antenna structure. More precisely, the transmitted electromagnetic wave is radiated by the RectAnt according to one of the radiation pat- terns in Figure 4, which then interacts with the scatterers that are spatially distributed in the environment. Depending on the radiation pattern being activated by the data stream to be transmitted, as a result, the received signal depends on the interaction between the spatial distribution of the scatterers and the directional characteristics of the antenna. In general, different radiation patterns interact with different scatterers, which results in a unique received signal (fingerprint) for eve- ry possible radiation pattern. The potential advantages of this approach compared with conventional SM lie in the possibility of realizing very compact Figure 4: Illustration of the encoding principle of RectAnt-SM (generic channel use). 14 ZREE N°2/2018 LES GRANDS PRIX 2017 DE LA SEE and low-complexity antennas that are inherently used for modulating data. In addition, the use of RectAnts may avoid the need of using mechanical switches, which, on the other hand, are replaced by appropriate circuits that are integrated in the antenna design and that are capable of modifying the distribution of the current of the RectAnt. These peculiarities are suitable for IoT applications. RectAnt-SM: From Theory to Practice – The ANR Project “SpatialModulation” Even though the idea of using RectAnts in the context of SM research was proposed in [7] just recently, several theoretical and experimental activities are now available. The RectAnt-SM technology is currently being researched and experimented by the author under the auspices of the ANR- funded research project titled “SpatialModulation”, which is coordinated by Orange Labs [13]. Notably, the team of resear- chers and engineers of the project has realized and imple- mented the world’s first visual demonstration of a testbed that adopts RectAnts for implementing the SM principle [14]. New RectAnts have been designed and have been used as a means for encoding the information bits. Their different energy patterns can be visualized with the aid of an inno- vative radio wave display that is capable of measuring the received power. The display shows that distinct received energy patterns are obtained if different radiation patterns of the RectAnts are activated at the transmitter. This world’s first demonstration was showcased at the Int. ITG Workshop on Smart Antennas in Berlin, Germany, in March 2017 and at the IEEE Int. Conference on Communications in Paris, France, in May 2017. Further information is available in [15]. Conclusion The emerging market of the IoT requires new energy-effi- cient and low-complexity MIMO-aided radio access technolo- gies. We have introduced and discussed a new radio access technology, conceived to satisfy the IoT requirements, that synergistically combines the potential of SM and RectAnts. The basic technology and current theoretical and experimen- tal research activities have been discussed. Notably, we have illustrated the recent innovations made in the context of the ANR-funded project “SpatialModulation” in terms of theore- tical, algorithmic, and implementation of this emerging and promising multi-antenna technology. References [1] M. Di Renzo et al., “GREENET - An early stage training network in enabling technologies for green radio,” IEEE L’AUTEUR Marco Di Renzo was born in L’Aquila, Italy, in 1978. He received the Laurea (cum laude) and Ph.D. degrees in electrical engineering from the University of L’Aquila, Italy, in 2003 and 2007, respectively, and the Habili- tation à Diriger des Recherches from University Paris- Sud, France, in 2013. Since 2010, he has been a Chargé de Recherche CNRS in the Laboratory of Signals and Systems (L2S) of Paris-Saclay University. He serves as the associate editor-in-chief of IEEE Communica- tions Letters, and as an editor of IEEE Transactions on Communications, and IEEE Transactions on Wireless Communications. He is a distinguished lecturer of the IEEE Vehicular Technology Society and IEEE Commu- nications Society, and a Senior Member of the IEEE. He is a recipient of several awards, including the 2013 IEEE COMSOC Best Young Researcher award (EMEA), the 2013 NoE-NEWCOM# Best Paper award, the 2015 IEEE Jack Neubauer Memorial award, and six Best Paper awards at IEEE conferences. REE N°2/2018 Z 15 Spatial Modulation for Multiple-Antenna Communication Veh. Technol. Conf. - Workshops, pp. 1–5, May 2011. [2] M. Di Renzo, H. Haas, and P. M. Grant, “Spatial modulation for multiple-antenna wireless systems: A survey,” IEEE Commun. Mag., vol. 49, no. 12, pp. 182–191, Dec. 2011. [3] A. Stavridis, S. Sinanovic, M. Di Renzo, and H. Haas, “Energy evaluation of spatial modulation at a multi-antenna base station,” IEEE Veh. Technol. Conf. - Fall, pp. 1–5, Sep. 2013. [4] M. Di Renzo and H. Haas, “Bit error probability of SM- MIMO over generalized fading channels,” IEEE Trans. Veh. Technol., vol. 61, no. 3, pp. 1124–1144, Mar. 2012. [5] A. Younis, S. Sinanovic, M. Di Renzo, R. Y. Mesleh, and H. Haas,“Generalisedspheredecodingforspatialmodulation,” IEEE Trans. Commun., vol. 61, no. 7, pp. 2805–2815, July 2013. [6] M. Di Renzo and H. Haas, “On transmit-diversity for spatial modulation MIMO: Impact of spatial-constellation diagram and shaping filters at the transmitter,” IEEE Trans. Veh. Technol., vol. 62, no. 6, pp. 2507–2531, July 2013.