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

The BER Analysis of MRC-aided Greedy Detection for OFDM-IM in Presence of Uncertain CSI

This letter investigates the bit error rate (BER) performance of orthogonal frequency division multiplexing index modulation, employing the maximal ratio combining-based low-complexity greedy detector (MRC-GD) and the PSK modulation. For performance analysis, we derive tight expressions for both index error probability (IEP) and BER, taking into account channel state information (CSI) uncertainty. This provides insight into various impacts of CSI uncertainty on the diversity gain and error floor of the IEP and the BER, respectively. We clearly show that under imperfect CSI, the MRC-aided GD can perform like the MRC-maximum likelihood detector, at lower complexity. Finally, simulation results are presented to verify the accuracy of derived expressions and the theoretical analysis

Compressive Sensing-Based Grant-Free Massive Access for 6G Massive Communication

The advent of the sixth-generation (6G) of wireless communications has given rise to the necessity to connect vast quantities of heterogeneous wireless devices, which requires advanced system capabilities far beyond existing network architectures. In particular, such massive communication has been recognized as a prime driver that can empower the 6G vision of future ubiquitous connectivity, supporting Internet of Human-Machine-Things for which massive access is critical. This paper surveys the most recent advances toward massive access in both academic and industry communities, focusing primarily on the promising compressive sensing-based grant-free massive access paradigm. We first specify the limitations of existing random access schemes and reveal that the practical implementation of massive communication relies on a dramatically different random access paradigm from the current ones mainly designed for human-centric communications. Then, a compressive sensing-based grant-free massive access roadmap is presented, where the evolutions from single-antenna to large-scale antenna array-based base stations, from single-station to cooperative massive multiple-input multiple-output systems, and from unsourced to sourced random access scenarios are detailed. Finally, we discuss the key challenges and open issues to shed light on the potential future research directions of grant-free massive access.Comment: Accepted by IEEE IoT Journa

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

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

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Novel feedback and signalling mechanisms for interference management and efficient modulation

In order to meet the ever-growing demand for mobile data, a number of different technologies have been adopted by the fourth generation standardization bodies. These include multiple access schemes such as spatial division multiple access (SDMA), and efficient modulation techniques such as orthogonal frequency division multiplexing (OFDM)-based modulation. The specific objectives of this theses are to develop an effective feedback method for interference management in smart antenna SDMA systems and to design an efficient OFDM-based modulation technique, where an additional dimension is added to the conventional two-dimensional modulation techniques such as quadrature amplitude modulation (QAM). In SDMA time division duplex (TDD) systems, where channel reciprocity is maintained, uplink (UL) channel sounding method is considered as one of the most promising feedback methods due to its bandwidth and delay efficiency. Conventional channel sounding (CCS) only conveys the channel state information (CSI) of each active user to the base station (BS). Due to the limitation in system performance because of co-channel interference (CCI) from adjacent cells in interference-limited scenarios, CSI is only a suboptimal metric for multiuser spatial multiplexing optimization. The first major contribution of this theses is a novel interference feedback method proposed to provide the BS with implicit knowledge about the interference level received by each mobile station (MS). More specifically, it is proposed to weight the conventional channel sounding pilots by the level of the experienced interference at the user’s side. Interference-weighted channel sounding (IWCS) acts as a spectrally efficient feedback technique that provides the BS with implicit knowledge about CCI experienced by each MS, and significantly improves the downlink (DL) sum capacity for both greedy and fair scheduling policies. For the sake of completeness, a novel procedure is developed to make the IWCS pilots usable for UL optimization. It is proposed to divide the optimization metric obtained from the IWCS pilots by the interference experienced at the BS’s antennas. The resultant new metric, the channel gain divided by the multiplication of DL and UL interference, provides link-protection awareness and is used to optimize both UL and DL. Using maximum capacity scheduling criterion, the link-protection aware metric results in a gain in the median system sum capacity of 26.7% and 12.5% in DL and UL respectively compared to the case when conventional channel sounding techniques are used. Moreover, heuristic algorithm has been proposed in order to facilitate a practical optimization and to reduce the computational complexity. The second major contribution of this theses is an innovative transmission approach, referred to as subcarrier-index modulation (SIM), which is proposed to be integrated with OFDM. The key idea of SIM is to employ the subcarrier-index to convey information to the receiver. Furthermore, a closed-form analytical bit error ratio (BER) of SIM OFDM in Rayleigh channel is derived. Simulation results show BER performance gain of 4 dB over 4-QAM OFDM for both coded and uncoded data without power saving policy. Alternatively, power saving policy maintains an average gain of 1 dB while only using half OFDM symbol transmit power