Generalized Spatial Modulation in Large-Scale Multiuser MIMO Systems
19 Mar 2015-IEEE Transactions on Wireless Communications (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC)-Vol. 14, Iss: 7, pp 3764-3779
TL;DR: In this article, an average bit error probability (ABEP) analysis for maximum likelihood detection in multiuser GSM-MIMO on the uplink, where an upper bound on the ABEP was derived, and low-complexity algorithms for signal detection and channel estimation at the base station receiver based on message passing were proposed.
Abstract: Generalized spatial modulation (GSM) uses $n_{t} $ transmit antenna elements but fewer transmit radio frequency (RF) chains, $n_{rf} $ . Spatial modulation (SM) and spatial multiplexing are special cases of GSM with $n_{rf}=1$ and $n_{rf}=n_{t} $ , respectively. In GSM, in addition to conveying information bits through $n_{rf} $ conventional modulation symbols (for example, QAM), the indices of the $n_{rf} $ active transmit antennas also convey information bits. In this paper, we investigate GSM for large-scale multiuser MIMO communications on the uplink. Our contributions in this paper include: 1) an average bit error probability (ABEP) analysis for maximum-likelihood detection in multiuser GSM-MIMO on the uplink, where we derive an upper bound on the ABEP, and 2) low-complexity algorithms for GSM-MIMO signal detection and channel estimation at the base station receiver based on message passing. The analytical upper bounds on the ABEP are found to be tight at moderate to high signal-to-noise ratios (SNR) . The proposed receiver algorithms are found to scale very well in complexity while achieving near-optimal performance in large dimensions. Simulation results show that, for the same spectral efficiency, multiuser GSM-MIMO can outperform multiuser SM-MIMO as well as conventional multiuser MIMO, by about 2 to 9 dB at a bit error rate of $10^{-3} $ . Such SNR gains in GSM-MIMO compared to SM-MIMO and conventional MIMO can be attributed to the fact that, because of a larger number of spatial index bits, GSM-MIMO can use a lower-order QAM alphabet which is more power efficient.
Citations
More filters
TL;DR: Three forms of IM are investigated: spatial modulation, channel modulation and orthogonal frequency division multiplexing (OFDM) with IM, which consider the transmit antennas of a multiple-input multiple-output system, the radio frequency mirrors mounted at a transmit antenna and the subcarriers of an OFDM system for IM techniques, respectively.
Abstract: What is index modulation (IM)? This is an interesting question that we have started to hear more and more frequently over the past few years. The aim of this paper is to answer this question in a comprehensive manner by covering not only the basic principles and emerging variants of IM, but also reviewing the most recent as well as promising advances in this field toward the application scenarios foreseen in next-generation wireless networks. More specifically, we investigate three forms of IM: spatial modulation, channel modulation and orthogonal frequency division multiplexing (OFDM) with IM, which consider the transmit antennas of a multiple-input multiple-output system, the radio frequency mirrors (parasitic elements) mounted at a transmit antenna and the subcarriers of an OFDM system for IM techniques, respectively. We present the up-to-date advances in these three promising frontiers and discuss possible future research directions for IM-based schemes toward low-complexity, spectrum- and energy-efficient next-generation wireless networks.
676 citations
TL;DR: A survey on IM is presented to provide the readers with a better understanding of its principles, advantages, and potential applications and a range of challenges and open issues on IM are discussed.
Abstract: In fifth generation wireless networks, the escalating teletraffic and energy consumption has necessitated the development of green communication techniques in order to further enhance both the system’s spectral efficiency and energy efficiency In the past few years, the novel index modulation (IM) has emerged as a promising technology that is widely employed in wireless communications In this paper, we present a survey on IM in order to provide the readers with a better understanding of its principles, advantages, and potential applications We start with a comprehensive literature review, where the concept of IM is introduced, and various existing IM schemes are classified according to their signal domains, including the frequency domain, spatial domain, time domain and channel domain Then the principles of different IM-aided systems are detailed, where the transceiver design is illustrated, followed by descriptions of typical systems and corresponding performance evaluation A range of challenges and open issues on IM are discussed before we conclude this survey
243 citations
TL;DR: A comprehensive overview of the latest research achievements of SC-SM is presented, which outlines the associated transceiver design, the benefits and potential tradeoffs, the LSA aided multiuser (MU) transmission developments, the relevant open research issues as well as the potential solutions of this appealing transmission technique.
Abstract: The main limitations of employing large-scale antenna (LSA) architectures for broadband frequency-selective channels include, but are not limited to their complexity, power consumption, and the high cost of multiple radio frequency (RF) chains. Promising solutions can be found in the recently proposed family of single-carrier (SC) spatial modulation (SM) transmission techniques. Since the SM scheme’s transmit antenna (TA) activation process is carried out in the context of a SC-SM architecture, the benefits of a low-complexity and low-cost single-RF transmitter are maintained, while a high MIMO multiplexing gain can be attained. Moreover, owing to its inherent SC structure, the transmit signals of SC-SM have attractive peak power characteristics and a high robustness to RF hardware impairments, such as the RF carrier frequency offset (CFO) and phase noise. In this paper, we present a comprehensive overview of the latest research achievements of SC-SM, which has recently attracted considerable attention. We outline the associated transceiver design, the benefits and potential tradeoffs, the LSA aided multiuser (MU) transmission developments, the relevant open research issues as well as the potential solutions of this appealing transmission technique.
202 citations
TL;DR: This work intrinsically amalgamate SM and NOMA to conceive a new system component exhibiting distinct benefits in the V2V scenarios considered, and investigates the bit error ratio performance of N OMA-SM via Monte Carlo simulations.
Abstract: At the time of writing, vehicle-to-vehicle (V2V) communication is enjoying substantial research attention as a benefit of its compelling applications. However, the ever-increasing tele-traffic is expected to result in overcrowding of the available band. As a first resort, multiple input multiple output (MIMO) can be utilized to enhance the attainable bandwidth efficiency or link reliability. However, in hostile V2V wireless propagation environments, the achievable multiple-antenna gain is eroded by the channel correlation. As a promising MIMO technique, spatial modulation (SM) only activates a single transmit antenna (TA) in any symbol interval and, hence, completely avoids the inter-antenna interference, hence showing robustness against channel correlation. As a further powerful solution, non-orthogonal multiple access (NOMA) has been proposed for improving the bandwidth efficiency. Inspired by the robustness of SM against channel correlation and the benefits of NOMA, we intrinsically amalgamate them into NOMA-SM in order to deal with the deleterious effects of wireless V2V environments as well as to support improved bandwidth efficiency. Moreover, the bandwidth efficiency of NOMA-SM is further boosted with the aid of a massive TA configuration. Specifically, a spatio-temporally correlated Rician channel is considered for a V2V scenario. We investigate the bit error ratio performance of NOMA-SM via Monte Carlo simulations, where the impact of the Rician $K$ -factor, spatial correlation of the antenna array, time-varying effect of the V2V channel, and the power allocation factor is discussed. Furthermore, we also analyze the capacity of NOMA-SM. By analyzing the capacity and deriving closed-form upper bounds on the capacity, a pair of power allocation optimization schemes are formulated. The optimal solutions are demonstrated to be achievable with the aid of our proposed algorithm. Again, instead of simply invoking a pair of popular techniques, we intrinsically amalgamate SM and NOMA to conceive a new system component exhibiting distinct benefits in the V2V scenarios considered.
148 citations
TL;DR: This letter generalizes the precoding-aided spatial modulation (PSM) to a multiuser (MU) downlink scenario and issues of detection algorithms and a lower bound of secrecy rate are addressed to verify security enhancement in the proposed scheme.
Abstract: This letter generalizes the precoding-aided spatial modulation (PSM) to a multiuser (MU) downlink scenario. With precoding vectors elaborately designed, a proposed MU-PSM scheme has the capability to resist a multiple antenna eavesdropper. Specifically, signal precoding matrices (SPMs) are designed to cancel the MU interference and modulate partial information bits on the indices of receive antennas. To improve physical layer security, scrambling on SPMs is conceived to construct a fast-varying precoding matrix, which contributes to the degradation at Eve’s blind estimation and detection. Moreover, issues of detection algorithms and a lower bound of secrecy rate are addressed to verify security enhancement in the proposed scheme.
63 citations
References
More filters
Book•
01 Jan 2005TL;DR: In this paper, the authors propose a multiuser communication architecture for point-to-point wireless networks with additive Gaussian noise detection and estimation in the context of MIMO networks.
Abstract: 1. Introduction 2. The wireless channel 3. Point-to-point communication: detection, diversity and channel uncertainty 4. Cellular systems: multiple access and interference management 5. Capacity of wireless channels 6. Multiuser capacity and opportunistic communication 7. MIMO I: spatial multiplexing and channel modeling 8. MIMO II: capacity and multiplexing architectures 9. MIMO III: diversity-multiplexing tradeoff and universal space-time codes 10. MIMO IV: multiuser communication A. Detection and estimation in additive Gaussian noise B. Information theory background.
8,084 citations
TL;DR: While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly joined terminals, the exploitation of extra degrees of freedom provided by the excess of service antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios.
Abstract: Multi-user MIMO offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multi-user MIMO, as originally envisioned, with roughly equal numbers of service antennas and terminals and frequency-division duplex operation, is not a scalable technology. Massive MIMO (also known as large-scale antenna systems, very large MIMO, hyper MIMO, full-dimension MIMO, and ARGOS) makes a clean break with current practice through the use of a large excess of service antennas over active terminals and time-division duplex operation. Extra antennas help by focusing energy into ever smaller regions of space to bring huge improvements in throughput and radiated energy efficiency. Other benefits of massive MIMO include extensive use of inexpensive low-power components, reduced latency, simplification of the MAC layer, and robustness against intentional jamming. The anticipated throughput depends on the propagation environment providing asymptotically orthogonal channels to the terminals, but so far experiments have not disclosed any limitations in this regard. While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly joined terminals, the exploitation of extra degrees of freedom provided by the excess of service antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios. This article presents an overview of the massive MIMO concept and contemporary research on the topic.
6,184 citations
TL;DR: The gains in multiuser systems are even more impressive, because such systems offer the possibility to transmit simultaneously to several users and the flexibility to select what users to schedule for reception at any given point in time.
Abstract: Multiple-input multiple-output (MIMO) technology is maturing and is being incorporated into emerging wireless broadband standards like long-term evolution (LTE) [1]. For example, the LTE standard allows for up to eight antenna ports at the base station. Basically, the more antennas the transmitter/receiver is equipped with, and the more degrees of freedom that the propagation channel can provide, the better the performance in terms of data rate or link reliability. More precisely, on a quasi static channel where a code word spans across only one time and frequency coherence interval, the reliability of a point-to-point MIMO link scales according to Prob(link outage) ` SNR-ntnr where nt and nr are the numbers of transmit and receive antennas, respectively, and signal-to-noise ratio is denoted by SNR. On a channel that varies rapidly as a function of time and frequency, and where circumstances permit coding across many channel coherence intervals, the achievable rate scales as min(nt, nr) log(1 + SNR). The gains in multiuser systems are even more impressive, because such systems offer the possibility to transmit simultaneously to several users and the flexibility to select what users to schedule for reception at any given point in time [2].
5,158 citations
TL;DR: Very large MIMO as mentioned in this paper is a new research field both in communication theory, propagation, and electronics and represents a paradigm shift in the way of thinking both with regards to theory, systems and implementation.
Abstract: This paper surveys recent advances in the area of very large MIMO systems.
With very large MIMO, we think of systems that use antenna arrays with an order of magnitude more elements than in systems being built today, say a hundred antennas or more. Very large MIMO entails an unprecedented number of antennas simultaneously serving a much smaller number of terminals. The disparity in number emerges as a desirable operating condition and a practical one as well. The number of terminals that can be simultaneously served is limited, not by the number of antennas, but rather by our inability to acquire channel-state information for an unlimited number of terminals. Larger numbers of terminals can always be accommodated by combining very large MIMO technology with conventional time- and frequency-division multiplexing via OFDM. Very large MIMO arrays is a new research field both in communication theory, propagation, and electronics and represents a paradigm shift in the way of thinking both with regards to theory, systems and implementation. The ultimate vision of very large MIMO systems is that the antenna array would consist of small active antenna units, plugged into an (optical) fieldbus.
2,717 citations
Book•
28 Jun 2004TL;DR: A tutorial on random matrices is provided which provides an overview of the theory and brings together in one source the most significant results recently obtained.
Abstract: Random matrix theory has found many applications in physics, statistics and engineering since its inception. Although early developments were motivated by practical experimental problems, random matrices are now used in fields as diverse as Riemann hypothesis, stochastic differential equations, condensed matter physics, statistical physics, chaotic systems, numerical linear algebra, neural networks, multivariate statistics, information theory, signal processing and small-world networks. This article provides a tutorial on random matrices which provides an overview of the theory and brings together in one source the most significant results recently obtained. Furthermore, the application of random matrix theory to the fundamental limits of wireless communication channels is described in depth.
2,308 citations