TCM for OFDM-IM

Orthogonal frequency division multiplexing (OFDM) with index modulation (IM) is a multicarrier transmission technique for frequency-selective fading channels. Although it is energy and spectral efficient, its performance may not be satisfactory as some active subcarriers can be suppressed by fading. In this letter, we consider trellis coded modulation (TCM) for OFDM-IM in order to improve the detection performance of active subcarriers by increasing the Hamming distance between index symbols. We devise mapping rules for TCM for two cases and it is shown that the diversity order can be improved, which results in a lower probability of index error

Deep Learning-Based Detector for OFDM-IM

This letter presents the first attempt of exploiting deep learning (DL) in the signal detection of orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. Particularly, we propose a novel DL-based detector termed as DeepIM, which employs a deep neural network with fully connected layers to recover data bits in an OFDM-IM system. To enhance the performance of DeepIM, the received signal and channel vectors are pre-processed based on the domain knowledge before entering the network. Using datasets collected by simulations, DeepIM is first trained offline to minimize the bit error rate (BER) and then the trained model is deployed for the online signal detection of OFDM-IM. Simulation results show that DeepIM can achieve a near-optimal BER with a lower runtime than existing hand-crafted detectors

Deep Energy Autoencoder for Noncoherent Multicarrier MU-SIMO Systems

We propose a novel deep energy autoencoder (EA) for noncoherent multicarrier multiuser single-input multipleoutput (MU-SIMO) systems under fading channels. In particular, a single-user noncoherent EA-based (NC-EA) system, based on the multicarrier SIMO framework, is first proposed, where both the transmitter and receiver are represented by deep neural networks (DNNs), known as the encoder and decoder of an EA. Unlike existing systems, the decoder of the NC-EA is fed only with the energy combined from all receive antennas, while its encoder outputs a real-valued vector whose elements stand for the subcarrier power levels. Using the NC-EA, we then develop two novel DNN structures for both uplink and downlink NC-EA multiple access (NC-EAMA) schemes, based on the multicarrier MUSIMO framework. Note that NC-EAMA allows multiple users to share the same sub-carriers, thus enables to achieve higher performance gains than noncoherent orthogonal counterparts. By properly training, the proposed NC-EA and NC-EAMA can efficiently recover the transmitted data without any channel state information estimation. Simulation results clearly show the superiority of our schemes in terms of reliability, flexibility and complexity over baseline schemes.Comment: Accepted, IEEE TW

A Variational Inference based Detection Method for Repetition Coded Generalized Spatial Modulation

In this paper, we consider a simple coding scheme for spatial modulation (SM), where the same set of active transmit antennas is repeatedly used over consecutive multiple transmissions. Based on a Gaussian approximation, an approximate maximum likelihood (ML) detection problem is formulated to detect the indices of active transmit antennas. We show that the solution to the approximate ML detection problem can achieve a full coding gain. Furthermore, we develop a low-complexity iterative algorithm to solve the problem with low complexity based on a well-known machine learning approach, i.e., variational inference. Simulation results show that the proposed algorithm can have a near ML performance. A salient feature of the proposed algorithm is that its complexity is independent of the number of active transmit antennas, whereas an exhaustive search for the ML problem requires a complexity that grows exponentially with the number of active transmit antennas.Comment: 11 pages, 8 figure

Cooperative OFDM-IM relays network with partial relay selection under imperfect CSI

In this paper, we investigate the performance of cooperative orthogonal frequency division multiplexing with index modulation (OFDM-IM) with the low complexity greedy detection (GD). In particular, we propose a novel partial relay selection scheme whose search criteria are designed to exploit the IM subcarriers. To provide low-complexity receiver, we further examine the energy-sensing based GD design for the cooperative OFDM-IM. For the performance analysis, we derive novel upper bound and approximate closed form solutions for both the average index error probability and the average symbol error probability over Nakagami-m fading channels with imperfect channel state information (CSI) at the relays and destination. Unlike the information theoretical works, in presence of positive detection error in the relays, the derived expressions provide a useful insight into the error performance of cooperative OFDM-IM under various fading conditions. The numerical and simulation results clearly present that the proposed scheme harmonizing partially selected relays and their IM subcarriers with GD can outperform the benchmark schemes, under uncertain CSI, at reduced complexity

Impact of CSI Uncertainty on the MCIK-OFDM Performance: Tight, Closed-Form Symbol Error Probability Analysis

This paper proposes a novel framework to analyze the symbol error probability (SEP) for multicarrier index keying orthogonal frequency-division multiplexing (MCIK-OFDM) systems. Considering two different types of detections such as the maximum likelihood (ML) and low-complexity greedy detectors (GD), we derive tight closed-form expressions for the average SEPs of MCIK-OFDM in the presence of channel state information (CSI) uncertainty. We undertake an asymptotic performance analysis with respect to three CSI conditions, which ensures to provide a comprehensive insight into the achievable diversity and coding gains as well as the impact of various CSI uncertainties on the SEP performance. The SEP performance comparison between the ML and GD is obtained under different CSI uncertainties. This interestingly reveals that the GD can achieve nearly optimal error performance as the M-ary modulation size is large or even outperforms the ML under certain CSI conditions. Finally, the theoretical and asymptotic analysis are verified via simulation results, obtaining the high accuracy of the derived SEP

Repeated MCIK-OFDM with Enhanced Transmit Diversity under CSI Uncertainty

This paper investigates the opportunity for a repetition coded multi-carrier index keying-orthogonal frequency division multiplexing (MCIK-OFDM), termed repeated MCIK-OFDM (ReMO), which can provide superior performance over existing schemes at the same spectral efficiency. Unlike the classical scheme, the proposed scheme activates a subset of subcarriers and modulates them with the same M-ary data symbol, while additional information is conveyed by the active sub-carrier indices. This approach not only provides the frequency diversity gains in the M-ary symbol detection but also improves the index detection, leading to considerable improvement in the transmit diversity. For performance analysis, we derive tight closed-form expressions for the symbol error probability and the bit error rate, under both perfect and imperfect channel state information (CSI). These expressions provide insight into the achievable performance gains, system designs, and impacts of various CSI conditions. Finally, simulation results are given to illustrate the superior performance achieved by our scheme over existing schemes under different CSI uncertainties

Spread OFDM-IM with precoding matrix and low-complexity detection designs

We propose a new spread orthogonal frequency division multiplexing with index modulation (S-OFDM-IM), which employs precoding matrices such as Walsh-Hadamard (WH) and Zadoff-Chu (ZC) to spread both non-zero data symbols of active sub-carriers and their indices, and then compress them into all available sub-carriers. This aims to increase the transmit diversity, exploiting both multipath and index diversities. As for the performance analysis, we derive the bit error probability (BEP) to provide an insight into the diversity and coding gains, and especially impacts of selecting various spreading matrices on these gains. This interestingly reveals an opportunity of using rotated versions of original WH and ZC matrices to further improve the BEP performance. More specifically, rotated matrices can enable S-OFDM-IM to harvest the maximum diversity gain, which is the number of sub-carriers, while benchmark schemes have diversity gains limited by two. Moreover, we propose three low-complexity detectors, namely minimum mean square error log-likelihood ratio, index pattern MMSE (IP-MMSE), and enhanced IP-MMSE, which achieve different levels of complexity and reliability. Simulation results are presented to prove the superiority of S-OFDM-IM over the benchmarks

Secure Index and Data Symbol Modulation for OFDM-IM

In this paper, we propose a secure index and data symbol modulation scheme for orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. By exploiting the notion of the channel reciprocity in time division duplexing mode over wireless channels for shared channel state information as a secret key, we investigate randomized mapping rules for index modulation as well as data symbol modulation. Due to the randomized mapping rules for index and data symbol modulation in OFDM-IM, an eavesdropper is not able to correctly decide message bits even though active subcarriers and their symbols are correctly estimated. In particular, we exploit a characteristic of OFDM-IM which uses a fraction of subcarriers for transmissions to enhance security of data symbol modulation. In addition, to design a set of mapping rules for data symbol modulation, we investigate both a random-selection-based set and a bit-mismatch-based set. Through the analysis and simulation results, we demonstrate that the proposed scheme based on the randomized mapping rules for index modulation and data symbol modulation has a better performance than an existing scheme (modified for OFDM-IM) in terms of bit error rate (BER) and successful attack probability. In particular, we can show that the BER at an eavesdropper is much higher if the bit-mismatch-based set of mapping rules is used

Set Partition Modulation

In this paper, a novel modulation scheme called set partition modulation (SPM) is proposed. In this scheme, set partitioning and ordered subsets in the set partitions are used to form codewords. We define different SPM variants and depict a practical model for using SPM with orthogonal frequency division multiplexing (OFDM). For the OFDM-SPM schemes, different constellations are used to distinguish between different subsets in a set partition. To achieve good distance properties as well as better error performance for the OFDM-SPM codewords, we define a codebook selection problem and formulate such a problem as a clique problem in graph theory. In this regard, we propose a fast and efficient codebook selection algorithm. We analyze error and achievable rate performance of the proposed schemes and provide asymptotic results for the performance. It is shown that the proposed SPM variants are general schemes, which encompass multi-mode OFDM with index modulation (MM-OFDM-IM) and dual-mode OFDM with index modulation (DM-OFDM-IM) as special cases. It is also shown that OFDM-SPM schemes are capable of exhibiting better error performance and improved achievable rate than conventional OFDM, OFDM-IM, DM-OFDM-IM, and MM-OFDM-IM.Comment: 13 pages, 7 figures, journal pape