We propose multi-mode spectrally efficient frequency division multiplexing with index modulation (MM-SEFDM), an enhanced non-orthogonal waveform that embeds distinct constellations on every subcarrier and conveys additional bits through subcarrier-index patterns. By compressing the subcarrier spacing of orthogonal frequency division multiplexing (OFDM), MM-SEFDM significantly improves spectral efficiency at the expense of controlled inter-carrier and inter-symbol interference. This joint non-orthogonal and multi-mode index modulation structure introduces significant detection complexity, necessitating a low-complexity, yet effective receiver capable of handling interference and permutation-based index-symbol decoding. To this end, we propose a two-phase Transformer-based decoder: in Phase 1, the network learns joint index–symbol constellations over AWGN channels, while in Phase 2, it continues training over Rayleigh fading channels to enhance robustness under realistic propagation conditions. Furthermore, to enhance model generalization, the detector is trained under domain randomization across different non-orthogonality levels and channel estimation errors (CSE), ensuring robust and SNR-agnostic performance under diverse interference and operating conditions. Compared to brute-force maximum-likelihood detection, the proposed learning-based decoder reduces inference complexity from exponential to polynomial time, while achieving near-optimal bit-error rate performance.

This article proposes two modulation schemes—binary polarized spatial modulation (BPSM) and permutation-based polarized spatial modulation (PPSM)—for multi-input multi-output systems employing polarized antennas. Unlike conventional spatial modulation techniques, which rely on partial antenna activation, the proposed schemes utilize all available transmit antennas with distinct polarization activation patterns to enhance spectral efficiency (SE) while reducing inter-antenna correlation. In BPSM, spatial bits are mapped to binary polarization states using dual-polarized antennas without permutations. PPSM extends this concept by employing permutation-based mapping over multiple polarization states and antennas, thereby allowing richer index information, particularly in systems with more than two polarization states or numerous transmit antennas. To enhance performance, singular value decomposition and particle swarm optimization are employed for optimal power allocation, maximizing channel capacity while adhering to practical constraints. Because of the high complexity of maximum likelihood detection, orthogonal matching pursuit is adopted as a low-complexity sparse recovery algorithm tailored to the inherent sparsity of the transmitted signal structure. The proposed schemes are analytically and numerically evaluated under Rayleigh and Rician fading channels by considering channel estimation errors and correlation effects. The results show that BPSM and PPSM offer favorable trade-offs between the SE and bit error rate, outperforming traditional spatial modulation schemes using both unpolarized and polarized antennas.

We propose a structured opportunistic spectrum access scheme, named ON-OFDM-IM, which employs non-orthogonal multiple access with orthogonal frequency division multiplexing and index modulation (OFDM-IM) to enable efficient spectrum reuse. The framework operates in two phases: an anchor transmission (AT) phase and a subsequent opportunistic access phase. During the first phase, anchor transmitters activate only a subset of subcarriers (SCs) and embed information through both the activation pattern and conventional constellation symbols to enhance energy efficiency. In the second phase, unlicensed devices opportunistically utilize the idle SCs left unused in the AT to support device-to-device communication. This article derives mathematical expressions for the spectral efficiency (SE) and bit error rate (BER) of ON-OFDM-IM. Analytical and simulation results confirm that the proposed scheme achieves a favorable trade-off between SE and BER, outperforming conventional benchmark systems.

This article introduces a massive multiple-input—multiple-output (mMIMO) system that utilizes spectrally efficient frequency division multiplexing (SEFDM) and incorporates a deep neural network (DNN) for enhanced SEFDM channel estimation. Unlike existing studies on DNN-based channel estimation, this research employs estimated channel feedback to dynamically adjust SEFDM signal characteristics at the transmitter, thereby improving the system’s adaptability. This adaptive mechanism optimizes the SEFDM compression value and modulation order based on real-time channel conditions, significantly enhancing the symbol error rate (SER). Detailed simulations demonstrate that higher modulation techniques experience substantial performance degradation with increased subcarrier compression in SEFDM. The proposed DNN-based channel estimation and adaptive parameter selection outperform traditional linear schemes, utilizing a more stable SEFDM system to achieve significant spectral efficiency (SE) compared to conventional orthogonal frequency division multiplexing (OFDM).

This paper presents dual-mode index modulation for spectral efficient frequency division multiplexing (SEFDM-DM). SEFDM is a non-orthogonal multicarrier technique created by compressing the subcarrier spacing of classical orthogonal frequency-division multiplexing (OFDM). SEFDM provides high spectrum efficiency (SE) at the expense of increased inter-carrier interference (ICI). SEFDM with index modulation (SEFDM-IM) has two information-bearing units, that is, a subcarrier activation pattern and modulated symbols, which reduce ICI at the expense of an SE deficit owing to inactive subcarriers. The proposed SEFDM-DM uses all available subcarriers while retaining the diversity gain of index modulation (IM). It enhances SE by transmitting distinct constellation modes through a subcarrier index selection mechanism. This study also presents SEFDM-DM with coordinate interleaving (SEFDM-CDM), which introduces space-time block codes with coordinate interleaving to enhance transmission diversity by sending real and imaginary parts of the constellation symbols over different subcarriers. Analytical and simulation results corroborate the benefits of the suggested work in terms of SE and bit error rate.