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Index Modulation Techniques for 5G Wireless Networks

Ertugrul Basar

arXiv:1604.08315v1cs.IT

TL;DR

5G’s targets for data rates, spectral efficiency, and energy efficiency motivate alternatives to existing physical-layer techniques. This article reviews index modulation for MIMO and multicarrier systems, emphasizing SM and OFDM-IM, their variants, applications, trade-offs, and research directions. It concludes that IM schemes are possible 5G candidates because they offer trade-offs among error performance, complexity, and spectral efficiency, while important challenges remain.

  • Problem

    5G wireless networks require new physical-layer solutions to support ambitious data-rate, spectral-efficiency, and energy-efficiency objectives.

  • Method

    The article reviews the principles, advances, implementation scenarios, and future directions of IM, focusing on SM and OFDM-IM for MIMO and multicarrier communications.

  • Results

    The review identifies IM schemes as possible 5G candidates and reports trade-offs involving error performance, complexity, and spectral efficiency.

  • Takeaways & Limitations

    IM offers low-complexity, spectrally efficient, and energy-efficient approaches for single- and multicarrier, massive MU-MIMO, and cooperative communications.

Abstract

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The increasing demand for higher data rates, better quality of service, fully mobile and connected wireless networks lead the researchers to seek new solutions beyond 4G wireless systems. It is anticipated that 5G wireless networks, which are expected to be introduced around 2020, will achieve ten times higher spectral and energy efficiency than current 4G wireless networks and will support data rates up to 10 Gbps for low mobility users. The ambitious goals set for 5G wireless networks require dramatic changes in the design of different layers for next generation communications systems. Massive multiple-input multiple-output (MIMO) systems, filter bank multi-carrier (FBMC) modulation, relaying technologies, and millimeter-wave communications have been considered as some of the strong candidates for the physical layer design of 5G networks. In this article, we shed light on the potential and implementation of index modulation (IM) techniques for MIMO and multi-carrier communications systems which are expected to be two of the key technologies for 5G systems. Specifically, we focus on two promising applications of IM: spatial modulation (SM) and orthogonal frequency division multiplexing with IM (OFDM-IM), and we discuss the recent advances and future research directions in IM technologies towards spectral and energy-efficient 5G wireless networks.

I. INTRODUCTION

The article introduces index modulation (IM), focusing on spatial modulation (SM) and OFDM-IM as candidate techniques for spectrally and energy-efficient 5G wireless systems. It reviews their principles, implementation scenarios, advances, trade-offs, and research directions.

  • I. INTRODUCTION: Index modulation conveys additional information through the indices of communication-system building blocks, complementing conventional signal modulation.The article focuses on antenna indices in SM and subcarrier indices in OFDM-IM.
  • I. INTRODUCTION: The article reviews SM and OFDM-IM principles, recent results, generalized and enhanced variants, and applications in massive MU-MIMO and cooperative communications.It also outlines implementation scenarios and future research directions for 5G networks.
  • II. INDEX MODULATION FOR TRANSMIT ANTENNAS: SPATIAL MODULATION: SM transmits information using both the active transmit-antenna index and an M-ary constellation symbol.The incoming bits are divided between constellation modulation and transmit-antenna selection.
  • II. INDEX MODULATION FOR TRANSMIT ANTENNAS: SPATIAL MODULATION: SM uses a single active transmit antenna, enabling one RF chain while eliminating inter-antenna synchronization and inter-channel interference.Its receiver must detect both the antenna index and transmitted symbol, with decoding complexity growing linearly with constellation size and transmit-antenna count.
  • II. INDEX MODULATION FOR TRANSMIT ANTENNAS: SPATIAL MODULATION: 46% improvement in energy efficiency in Mbits/J compared to V-BLAST is reported for multiple-antenna base stations.At fixed spectral efficiency, SM also achieves a 200(nT −1)/(2nT +1)% reduction in ML detection complexity compared to V-BLAST.
  • II. INDEX MODULATION FOR TRANSMIT ANTENNAS: SPATIAL MODULATION: SM’s spectral efficiency grows logarithmically with nT, requires sufficiently different antenna channels, and cannot provide transmit diversity in plain form.These constraints imply a trade-off among complexity, spectral efficiency, and error performance.

III. RECENT ADVANCES IN SM

Recent SM research extends the basic scheme through generalized, enhanced, and quadrature variants and explores diversity, adaptation, channel effects, and cooperative and massive MU-MIMO systems.

  • III. RECENT ADVANCES IN SM: Recent SM studies examine transmit and time diversity, adaptive modulation, antenna selection, precoding, fading channels, and channel-estimation errors.They also include information-theoretic analyses and differential SM with non-coherent detection.
  • III. RECENT ADVANCES IN SM: The article reviews generalized, enhanced, and quadrature SM, along with massive MU-MIMO and cooperative SM systems, as potential 5G solutions.These directions target efficient operation in next-generation wireless networks.

A. Generalized, Enhanced, and Quadrature SM Schemes

Generalized, enhanced, and quadrature spatial modulation variants address classical SM’s spectral-efficiency limitations by using multiple active antennas, multiple constellations, or separate signal components.

  • Classical SM has lower spectral efficiency than V-BLAST because inactive transmit antennas limit information transmission.
  • Generalized SM: GSM selects multiple active antennas transmitting the same symbol, relaxing classical SM’s power-of-two antenna constraint and increasing spatial-domain bits.
  • Multiple-active SM: MA-SM transmits different symbols from selected antennas and provides an intermediate solution between SM with nA = 1 and V-BLAST with nA = nT.
  • Enhanced SM: ESM conveys information through joint selection of active antennas and signal constellations, allowing variable numbers of active antennas per signaling interval.
  • Enhanced SM: For two transmit antennas at 4 bpcu, ESM uses QPSK and BPSK variants to represent four two-bit sequences through different transmission vectors.

TRANSMITTED BY THE SPATIAL DOMAIN FOR ESM AND QSM

QSM separately applies spatial modulation to the real and imaginary components of complex symbols, while ESM and QSM increase spatial-domain information compared with conventional SM.

  • Quadrature SM: QSM separately transmits the real and imaginary parts of complex M-ary symbols using the spatial-modulation principle.
  • Quadrature SM: QSM achieves 2 log2(nT)+log2(M) bpcu by independently applying spatial modulation to in-phase and quadrature components.
  • Quadrature SM: QSM can use one or two active antennas while retaining a single RF chain because transmission uses only cosine and sine carriers.
  • ESM and QSM convey more spatial-domain bits than conventional SM, improving spectral and energy efficiency.
  • QSM and ESM have equal dmin at 4 and 6 bpcu, but QSM has worse dmin and error performance at higher spectral efficiencies while ESM requires two RF chains.

B. Massive Multi-user MIMO Systems with SM

Massive MU-MIMO creates opportunities to use spatial modulation for additional spatial-domain bits with few RF chains, supporting both uplink and downlink implementations but introducing detection complexity.

  • Massive MIMO can increase spatial-domain information bits for SM even when available RF chains are very limited.
  • SM offers an easy and cheap implementation for massive MIMO, although its spectral efficiency remains below traditional V-BLAST.
  • SM suits unbalanced massive-MIMO configurations in which the number of receive antennas is smaller than the number of transmit antennas.
  • Uplink: In uplink massive MU-MIMO, users can transmit additional information through SM without increasing system complexity compared with single-antenna terminals.
  • Detection and extensions: GSM, ESM, and QSM can be implemented at users to further improve spectral efficiency, while ML detection at the base station has complexity that increases exponentially with the number of users.

C. Cooperative SM Systems

Cooperative spatial modulation combines SM with relaying and distributed cooperation to create implementation options, diversity gains, and higher data rates without increasing mobile or relay-terminal cost and complexity.

  • Cooperative SM combines spatial modulation and cooperative communications to provide implementation scenarios, additional diversity gains, and higher data rates.
  • Dual-hop SM: Dual-hop cooperative SM can use SM at source and relay with decode-and-forward or amplify-and-forward relaying when source and destination lack a direct link.
  • Network-coded SM: Network-coded SM reduces two-way source–destination transmission from four phases to two by combining signals at the relay.
  • Distributed SM: Distributed SM lets relay indices convey information, allowing cooperation among single-antenna relays and supporting opportunistic relay selection.
  • GSM, ESM, and QSM can be added to cooperative scenarios to improve spectral efficiency and increase design flexibility.

IV. INDEX MODULATION FOR OFDM SUBCARRIERS: OFDM WITH INDEX MODULATION

OFDM-IM conveys information through both active-subcarrier indices and M-ary symbols, allowing adjustable activation patterns and a tunable trade-off between spectral efficiency and error performance. Its transmitter constructs interleaved OFDM-IM frames, while receivers detect subcarrier activity and symbols using ML or lower-complexity LLR methods.

  • OFDM-IM splits incoming bits between subcarrier-index selection and M-ary constellation symbols, activating only a subset of available subcarriers.
  • Transmitter structure: For each frame, OFDM-IM forms N-subcarrier subblocks, concatenates them into an NF-subcarrier frame, optionally interleaves blocks, then applies IFFT, CP insertion, and DAC conversion.The transmitted bits satisfy p = p1 + p2 and p2 = K log2 M.
  • Index selection: Index selection uses look-up tables for smaller N and combinatorial number theory for higher N, with receiver processing matched to the selected procedure.
  • Receiver structure: The near-optimal LLR detector first estimates active subcarriers probabilistically and then detects their data symbols, avoiding the joint search required by ML detection.
  • OFDM-IM adjusts active-subcarrier count to target spectral efficiency or error performance and can improve BER over classical OFDM at low-to-mid spectral efficiencies with comparable near-optimal decoding complexity.The paper also reports that OFDM-IM outperforms classical OFDM in ergodic achievable rate.

V. RECENT ADVANCES IN OFDM-IM

Recent OFDM-IM advances generalize activation patterns and apply index modulation independently to in-phase and quadrature components. These designs increase flexibility and, in the OFDM-GIM-II example, raise bits per subblock by 37.5% over OFDM-IM.

  • OFDM-GIM-I: OFDM-GIM-I allows the number of active subcarriers to vary with the information bits instead of remaining fixed.
  • OFDM-GIM-II: OFDM-GIM-II applies index modulation independently to in-phase and quadrature components, allowing a subcarrier to be active for one component while inactive for the other.
  • OFDM-GIM-II: 37.5% higher bits per subblock: OFDM-GIM-II transmits 44 bits versus 32 bits for OFDM-IM in the stated N = 16, K = 10, QPSK example.

B. From SISO-OFDM-IM to MIMO-OFDM-IM

MIMO-OFDM-IM combines parallel SISO-OFDM-IM transmitters with MIMO detection to improve error performance while retaining flexible design. Simulations report SNR gains over classical MIMO-OFDM at equal spectral efficiency, while low-complexity detection for GSFIM remains open.

  • MIMO-OFDM-IM combines OFDM-IM with nT × nR MIMO transmission through parallel concatenated SISO-OFDM-IM transmitters.
  • Its receiver separates simultaneous frames and uses low-complexity MMSE detection with LLR calculations based on filtered received-signal statistics.
  • Significant SNR improvements: MIMO-OFDM-IM reaches target uncoded BER values with less SNR than classical V-BLAST-type MIMO-OFDM at equal spectral efficiency.The comparison covers 2×2, 4×4, and 8×8 MIMO configurations.
  • GSFIM: GSFIM combines spatial and frequency-domain index modulation and improves achievable data rate and BER over MIMO-OFDM with ML detection for BPSK and QPSK.Low-complexity detector design for GSFIM remains an open research problem.

VI. CONCLUSIONS AND FUTURE WORK

The article identifies index modulation as a promising approach for 5G because it offers trade-offs among spectral efficiency, error performance, and complexity. It also highlights unresolved research challenges in generalized schemes, massive MU-MIMO, cooperative communications, and practical implementation.

  • Conclusions: Lower-complexity near/sub-optimal detection is possible for some IM schemes, although optimal detection may remain costly.The table material specifically notes the availability of lower-complexity near/sub-optimal detection.
  • Conclusions: IM schemes offer trade-offs among error performance, detection complexity, and spectral efficiency that make them possible 5G candidates.These trade-offs are summarized through the reviewed schemes’ pros and cons.
  • Future research: Future work includes generalized and enhanced IM schemes with higher efficiency, lower transceiver complexity, and better error performance.The proposed direction targets simultaneous improvements across these design objectives.
  • Future research: Integrating SM, GSM, ESM, QSM, and OFDM-IM into massive MU-MIMO requires new uplink and downlink transmission protocols.The integration target is explicitly framed for massive MU-MIMO systems in 5G networks.
  • Future research: Future research should adapt IM to dual-hop, multi-hop, network-coded, multi-relay, and distributed cooperative networks.The article also calls for practical implementation studies of IM techniques.

BIOGRAPHY

Ertugrul Basar is an assistant professor at Istanbul Technical University and a member of its Wireless Communication Research Group.

  • Biography: Ertugrul Basar earned his B.S. degree from Istanbul University and his M.S. and Ph.D. degrees from Istanbul Technical University.He spent the 2011–2012 academic year at Princeton University’s Department of Electrical Engineering.
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