This article introduces non-orthogonal frequency and time index modulation multiple access (NFT-IMMA) for sixth-generation (6G) communications. The proposed NFT-IMMA increases the number of communication resources by utilizing power levels, frequency, and time slots as transmission entities, which are selected through a predefined index activation pattern derived from partial user input data. NFT-IMMA increases spectral efficiency (SE) by employing index information and classical constellation symbols as methods of data transmission. Notably, it does not require prior scheduling at the base station, which simplifies the coordination process. Additionally, the use of three-dimensional indices for resource selection helps reduce user collisions. Performance evaluation at the physical layer, focusing on SE and bit error rate, indicates that NFT-IMMA outperforms conventional index modulation (IM) multiple access and IM-based orthogonal frequency division multiple access. At the MAC layer, NFT-IMMA demonstrates superior performance in terms of throughput and packet loss rate when compared to ALOHA and other competing techniques.

This investigation introduces an uplink frequencytime (FT) index modulation multiple access (IMMA) (FT-IMMA) scheme designed to augment the spectral efficiency (SE) of conventional orthogonal frequency-division multiple access (OFDMA). The fundamental principle of this approach involves allocating FT resources within OFDMA to users through twodimensional index modulation (IM). A subset of input bits from each user dictates the indices of subcarriers and time slots within the FT resources of OFDMA, while the remaining bits undergo a conventional 𝑀-ary modulation. FT-IMMA obviates the necessity for a prior scheduling mechanism, thereby reducing communication overhead. While this grant-free access approach may potentially introduce data collisions within the system, the collision probability of the proposed model is observed to be markedly lower compared to traditional IMMA systems. However, the two-dimensional IM approach increases the computational complexity of conventional maximum likelihood detection. To address this, the authors propose using orthogonal matching pursuit, a compressive sensing technique that effectively reduces the computational burden. Through analytical investigation and simulation results, FT-IMMA demonstrates superior performance compared to its counterparts, showcasing notable advantages in both bit error rate and SE.