Maximal Spectral Efficiency of OFDM With Index Modulation Under Polynomial Space Complexity

Queiroz, Saulo; Silva, Wesley; Vilela, João P.; Monteiro, Edmundo

doi:10.1109/lwc.2020.2965533

Cited by 6 publications

(17 citation statements)

References 11 publications

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“…From this, the largest computational complexity T (N ) must satisfy lim N →∞ m(N )/T (N ) > 0, i.e., the SC throughput must not nullify as the system is assigned an arbitrarily large amount of spectrum. Based on that, in [43] we present the first mapper that supports all 2 log 2 ( N N/2 ) waveforms of OFDM-IM in the same asymptotic time of the classic OFDM mapper. However, that proposed mapper still requires an extra space of Θ(N 2 ) look-up table entries in comparison to the classic OFDM mapper.…”

Section: ) Novel Sp-free Ofdm-im Mappersmentioning

confidence: 97%

Optimal Mapper for OFDM With Index Modulation: A Spectro-Computational Analysis

2020

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In this work, we present an optimal mapper for OFDM with index modulation (OFDM-IM). By optimal we mean the mapper achieves the lowest possible asymptotic computational complexity (CC) when the spectral efficiency (SE) gain over OFDM maximizes. We propose the spectro-computational (SC) analysis to capture the trade-off between CC and SE and to demonstrate that an N -subcarrier OFDM-IM mapper must run in exact Θ(N ) time complexity. We show that an OFDM-IM mapper running faster than such complexity cannot reach the maximal SE whereas one running slower nullifies the mapping throughput for arbitrarily large N . We demonstrate our theoretical findings by implementing an open-source library that supports all DSP steps to map/demap an N -subcarrier complex frequency-domain OFDM-IM symbol. Our implementation supports different index selector algorithms and is the first to enable the SE maximization while preserving the same time and space asymptotic complexities of the classic OFDM mapper.

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Section: ) Novel Sp-free Ofdm-im Mappersmentioning

confidence: 97%

Optimal Mapper for OFDM With Index Modulation: A Spectro-Computational Analysis

2020

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“…In [20], the authors suggest that θ can be attained using queries of the binomial coefficient θκ−i+1 κ−i+1 as in (7) from PT of dimensions Ω × κ. As PT consists of the binomial coefficients θκ−i+1 κ−i+1 corresponding to all Ω and κ, henceforth, there is no need to evaluate them from scratch; which considerably reduces the complexity of the index mapping and de-mapping.…”

Section: B Index Mapping and De-mappingmentioning

confidence: 99%

“…As PT consists of the binomial coefficients θκ−i+1 κ−i+1 corresponding to all Ω and κ, henceforth, there is no need to evaluate them from scratch; which considerably reduces the complexity of the index mapping and de-mapping. The complexity of PT based index mapping and de-mapping algorithms is O(Ω) [20] and requires a LUT of dimensions Ω × κ to be buffered. However, the limiting condition for linear mapping and de-mapping, i.e., κ ≤ Ω/2 is not an issue for PT based approaches which makes them more effective.…”

Section: B Index Mapping and De-mappingmentioning

confidence: 99%

Enhanced Optical-OFDM With Index and Dual-Mode Modulation for Optical Wireless Systems

et al. 2020

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In this article, we introduce intensity modulation and direct detection compatible enhanced optical-orthogonal frequency division multiplexing with index modulation (EO-OFDM-IM) schemes. These approaches augment the spectral efficiency (SE) relative to classical counterparts by enlarging the index domain information using the so-called virtual sub-carriers. The classical O-OFDM-IM schemes do not necessarily enhance the SE because of low cardinality of IM complex-valued sub-carrier set which is limited by constraints like Hermitian symmetry. The index domain extension for EO-OFDM-IM schemes is achieved by replacing the complex-valued sub-carriers (as in O-OFDM-IM) by twice real-valued virtual sub-carriers. The realization of non-negative signals is based on precepts of classical O-OFDM approaches, that are direct current (DC) O-OFDM and asymmetrically clipped (AC) O-OFDM. Thus, we refer to the EO-OFDM-IM approaches as DCEO-OFDM-IM and ACEO-OFDM-IM. We shall establish that in addition to improving SE, EO-OFDM-IM schemes provide extended granularity effectuating better SE/energy efficiency (EE) trade-off and improved bit error rate performance over classical counterparts. The EO-OFDM-IM schemes, however, are suitable for lower alphabet cardinalities of pulse-amplitude modulation making it difficult to attain high spectral efficiencies while maintaining EE. To circumvent this limitation, dual-mode (DM) counterparts, DCEO-OFDM-DM and ACEO-OFDM-DM are proposed. The numerical simulations shall demonstrate that the EO-OFDM-DM approaches are more energy and spectral efficient than classical O-OFDM-DM schemes and provide an advantageous granularity for EE/SE trade-off. Additionally, we use efficient index mapping and de-mapping algorithms based on Pascal's triangle, which allows investigating these approaches for peak SE by precluding the so-called sub-block partitioning. For peak SE, the use of optimal maximum-likelihood (ML) detector is cumbersome, therefore, we introduce two sub-optimal low-complexity detectors based on energy detection and ML criterion. INDEX TERMS Optical-orthogonal frequency-division multiplexing, index modulation, intensity modulation and direct detection, optical wireless systems.

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“…Particularly, the unique frequency domain embedded sparsity feature of OFDM-SIM signals is considered, which in turns allow hard and low-level clipping implementation without overhead or BER degradation. Accordingly, higher levels of PAPR reduction can be reached with the proposed scheme than clipping noise estimation-based techniques such as in [26,27]. Besides sparsity feature exploitation, prior-knowledge of the amplitudes of the activated/inactivated subcarriers are exploited by the proposed scheme to perform a low complex CS-based detection at RX.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, the double indexing on real/imaginary spaces is employed. The bit combinations are assumed to be sorted in a predefined order such as lexicographic order avoiding the exhaustive listing for all combinations such introduced in [27]. For each possible combination, the corresponding index can be simply expressed as follows [15,16]:…”

Section: A Ofdm-sim System Modelmentioning

confidence: 99%

Sparse Index OFDM Modulation for IoT Communications

et al. 2020

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One of the greatest challenges facing the physical layer design of the internet of things (IoT) resides in the imposed constraint of very low power consumption. Recently, new modulation scheme termed OFDM with sparse index modulation (OFDM-SIM) has been introduced as an energy efficient multicarrier scheme (MCS). Although of its high energy efficiency (EE) and spectral efficiency (SE), OFDM-SIM cannot fulfill the IoT energy requirements owing to its high PAPR. In this regard, an enhanced OFDM-SIM is proposed in this paper as an energy efficient MCS for IoT communications. In particular, a novel clippingcompressive sensing (CS) based PAPR reduction technique for OFDM-SIM is proposed. In the transmitter (TX) side, considering the complexity constraints for IoT devices, the simple and low complex clipping method is exploited to deal with the PAPR issue. On the receiver (RX) side, a robust CS signal recovery scheme is proposed to deal with tough resulting clipping noise. Unlike high complex conventional CS-based schemes, the proposed scheme exploits the inherent sparsity of the received enhanced OFDM-SIM signal rather than clipping noise sparsity to achieve a low complex CS signal detection. Moreover, in this paper, the information-theoretic limits on sparsity recovery are exploited to derive an upper bound measure of the bit error rate (BER). The simulation results demonstrate the superiority of the proposed scheme, as it significantly enhances the overall system performance in terms of EE and PAPR reduction compared to the conventional clipped coded-OFDM. INDEX TERMS IoT; OFDM-Sparse index modulation (OFDM-SIM); PAPR; Clipping; Compressive sensing (CS).

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Maximal Spectral Efficiency of OFDM With Index Modulation Under Polynomial Space Complexity

Cited by 6 publications

References 11 publications

Optimal Mapper for OFDM With Index Modulation: A Spectro-Computational Analysis

Optimal Mapper for OFDM With Index Modulation: A Spectro-Computational Analysis

Enhanced Optical-OFDM With Index and Dual-Mode Modulation for Optical Wireless Systems

Sparse Index OFDM Modulation for IoT Communications

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