Multidimensional Index Modulation in Wireless Communications

In index modulation schemes, information bits are conveyed through indexing of transmission entities such as antennas, subcarriers, times slots, precoders, subarrays, and radio frequency (RF) mirrors. Index modulation schemes are attractive for their advantages such as good performance, high rates, and hardware simplicity. This paper focuses on index modulation schemes in which multiple transmission entities, namely, {\em antennas}, {\em time slots}, and {\em RF mirrors}, are indexed {\em simultaneously}. Recognizing that such multidimensional index modulation schemes encourage sparsity in their transmit signal vectors, we propose efficient signal detection schemes that use compressive sensing based reconstruction algorithms. Results show that, for a given rate, improved performance is achieved when the number of indexed transmission entities is increased. We also explore indexing opportunities in {\em load modulation}, which is a modulation scheme that offers power efficiency and reduced RF hardware complexity advantages in multiantenna systems. Results show that indexing space and time in load modulated multiantenna systems can achieve improved performance

Multiuser Media-based Modulation for Massive MIMO Systems

Media-based modulation (MBM) is an attractive modulation scheme which is getting increased research attention recently. In this paper, we consider MBM for the uplink of a massive MIMO system, which has not been reported before. Each user is equipped with one transmit antenna with multiple radio frequency (RF) mirrors (parasitic elements) placed near it. The base station (BS) is equipped with tens to hundreds of receive antennas. We investigate the potential performance advantage of multiuser MBM (MU-MBM) in a massive MIMO setting. Our results show that multiuser MBM (MU-MBM) can significantly outperform other modulation schemes. For example, a bit error performance achieved using 500 receive antennas at the BS in a massive MIMO system using conventional modulation can be achieved using just 128 antennas using MU-MBM. Even multiuser spatial modulation and generalized spatial modulation in the same massive MIMO settings require more than 200 antennas to achieve the same bit error performance. Also, recognizing that the MU-MBM signal vectors are inherently sparse, we propose an efficient MU-MBM signal detection scheme that uses compressive sensing based reconstruction algorithms like orthogonal matching pursuit (OMP), compressive sampling matching pursuit (CoSaMP), and subspace pursuit (SP)

Time-indexed Media-based Modulation

Media-based modulation (MBM) is a promising modulation scheme which is attracting recent research attention. In MBM, radio frequency (RF) mirrors are used to create a channel modulation alphabet based on the ON/OFF (i.e., transparent/opaque) status of these mirrors. The index of the mirror activation pattern in a channel use conveys information bits in addition to the bits conveyed through conventional modulation symbols. MBM has been shown to achieve improved performance compared to conventional modulation schemes. In this paper, we introduce time-slot indexing to MBM, which further improves the performance. The proposed time-indexed MBM (TI-MBM) is a block transmission scheme, where a time slot in a given frame can be used or unused, and the choice of the slots used for transmission conveys time-index bits. We study the proposed TI-MBM scheme in frequency-selective channels and show that TI-MBM achieves better performance compared to conventional MBM. Further, recognizing that the TI-MBM signal structure promotes sparsity, we exploit the use of sparse recovery algorithms for the detection of TI-MBM signals. We show that compressive sampling matching pursuit (CoSaMP) and subspace pursuit (SP) based TI-MBM signal detection can achieve significantly improved performance compared to conventional minimum mean square (MMSE) detection

MAP-Index Coded Media-Based Modulation

Mirror activation pattern (MAP) in media-based modulation (MBM) refers to the ON/OFF status of radio-frequency mirrors, which create different near field geometries for different ON/OFF combinations. In this letter, we introduce a novel coding scheme for MBM in which indices are assigned to MAPs, such that these indices are used as labels for the elements in a Galois field. The MAP indices are then coded across time, and the block transmission is carried out. The resulting signal set has good distance distribution, which leads to good bit error performance. Structured sparse matrix sketching-based signal detection algorithms for the proposed scheme are presented

Multidimensional Index Modulation in Wireless Communications

In index modulation schemes, information bits are conveyed through indexing of transmission entities, such as antennas, subcarriers, times slots, precoders, subarrays, and radio frequency (RF) mirrors. Index modulation schemes are attractive for their advantages, such as good performance, high rates, and hardware simplicity. This paper focuses on index modulation schemes in which multiple transmission entities, namely, antennas, time slots, and RF mirrors, are indexed simultaneously. Recognizing that such multidimensional index modulation schemes encourage sparsity in their transmit signal vectors, we propose efficient signal detection schemes that use compressive sensing based reconstruction algorithms. Results show that, for a given rate, improved performance is achieved when the number of indexed transmission entities is increased. We also explore indexing opportunities in load modulation (LM), which is a modulation scheme that offers power efficiency and reduced RF hardware complexity advantages in multiantenna systems. Results show that indexing time and RF mirrors in load modulated multiantenna systems can achieve improved performance. A stagewise algorithm based on message passing suited for the detection of indexed LM signals is also proposed