OFDM Inspired Waveforms for 5G

Farhang‐Boroujeny, Behrouz; Moradi, Hussein

doi:10.1109/comst.2016.2565566

Cited by 266 publications

(141 citation statements)

References 69 publications

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“…Note that some works have studied the joint use of OQAM and GFDM and proposed circular OQAM (COQAM) waveforms [36]. However, it has been shown that GFDM and COQAM achieve comparable performance in terms of asynchronous coexistence [37]. This leads us to leave COQAM out of the scope of our study and to consider GFDM only as an example of a circularly pulse-shaped waveform.…”

Section: A Candidate Waveforms Under Studymentioning

confidence: 99%

Enabling Asynchronous Machine-Type D2D Communication Using Multiple Waveforms in 5G

Sexton

Bodinier²,

Farhang

et al. 2018

IEEE Internet Things J.

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Abstract-In this paper, we explore the idea that 5G will permit the use of multiple waveforms, with each service employing a waveform that is best suited for it. We look at a 5G machinetype communication (MTC) scenario consisting of clustered user equipment employing device-to-device (D2D) communication, such as a smart factory with inter-communicating machinery. The overhead associated with synchronising a large number of machine-type D2D user equipment (DUE) comes at a cost that may render synchronous communication infeasible or undesirable. Based on this motivation, we consider multiple possible combinations of prominent 5G waveform candidates for cellular users and DUEs, examining the asynchronous performance of all waveforms under consideration and using the performance of synchronous OFDM as a baseline for comparison. Specifically, we focus on the coexistence of waveforms in which the ordinary cellular users employ OFDM for synchronous communication, as in LTE, and the machine-type DUEs, operating asynchronously, employ a different waveform. When DUEs employ FBMC/OQAM, the average achieved rate is marginally greater than the synchronous OFDM baseline case, and approximately 43% greater than the asynchronous OFDM case. This result is encouraging, as the benefits of asynchronous D2D communication could be enjoyed in MTC scenarios without suffering any performance reduction compared to the synchronous OFDM scenario. We then investigate how the relative performance of different waveform choices depends on the scenario by varying key parameters. Notably, for asynchronous communication, increasing the transmit power of DUEs results in diminishing benefits unless the DUEs employ a waveform that mitigates inter-device leakage interference.

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Section: A Candidate Waveforms Under Studymentioning

confidence: 99%

Enabling Asynchronous Machine-Type D2D Communication Using Multiple Waveforms in 5G

Sexton

Bodinier²,

Farhang

et al. 2018

IEEE Internet Things J.

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“…As can be seen, the OFDM technique is omnipresent in the 5G waveform proposals. The OFDM technique shall certainly remain as the root framework for the new 5G waveform design, with some optimization to support the new 5G requirements [18,19]. This paper makes use of the complex -fading channel to assess the bit error rate (BER) performance of a BPSKbased OFDM system.…”

Section: International Journal Of Antennas and Propagationmentioning

confidence: 99%

The Complexα-μFading Channel with OFDM Application

Freitas¹,

Bomfin²,

Souza³

et al. 2017

International Journal of Antennas and Propagation

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The aims of this paper are threefold: (i) to present a model for the complex -fading channel; (ii) to propose an efficient, simple, and general method to generate complex -samples; (iii) to make use of this channel in order to assess the bit error rate performance of an OFDM system. An analytical framework is then used, whose output is validated through Monte Carlo simulation. Several important conclusions concerning the system performance as a function of the channel parameters, namely, nonlinearity, clustering, and power imbalance of in-phase and quadrature components, are drawn.

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“…Moreover, the orthogonality of the subcarriers causes the efficient use of the bandwidth. This technique does not need any complicated hardware and can be implemented using effective signal processing techniques such as FFT and IFFT …”

Section: Introductionmentioning

confidence: 99%

Channel estimation based on learning automata for OFDM systems

Salehi

Majidi

Neda

2018

Int J Communication

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Summary The abundant benefits of Orthogonal Frequency‐Division Multiplexing and its high flexibility have resulted in its widespread applications in many telecommunication standards. One important parameter for improving wireless system's efficiency is the accurate estimation of channel state information. In the literatures, many techniques have been studied in order to estimate the channel state information. Nowadays, the techniques based on intelligent algorithms such as genetic algorithm and particle swarm optimization (PSO) have attracted attention of researchers. With a very low pilot overhead, these techniques are able to estimate the channel frequency response properly only using the received signals. Unfortunately, each of these techniques suffers a common weakness: they have a slow convergence rate. In this paper, a new intelligent and different method has been presented for channel estimation using learning automata, entitled LA estimator, where the learning automata are search agents, and each pair is responsible for searching 1 complex coefficient of the channel frequency response. This method can achieve an accurate channel estimation with a moderate computational complexity in comparison with GA and PSO estimators. Furthermore, with higher convergence rate, our proposed method is capable of providing the same performance as GA and PSO. For a 2‐path fast fading channel, simulation results demonstrate the robustness of our proposed scheme according to the bit error rate and the mean square error.

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OFDM Inspired Waveforms for 5G

Cited by 266 publications

References 69 publications

Enabling Asynchronous Machine-Type D2D Communication Using Multiple Waveforms in 5G

Enabling Asynchronous Machine-Type D2D Communication Using Multiple Waveforms in 5G

The Complexα-μFading Channel with OFDM Application

Channel estimation based on learning automata for OFDM systems

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