Capacity Bounds for MIMO Microwave Backhaul Links Affected by Phase Noise

Durisi, Giuseppe; Tarable, Alberto; Camarda, Christian; Devassy, Rahul; Montorsi, G.

doi:10.1109/tcomm.2014.012014.130745

Cited by 35 publications

(41 citation statements)

References 30 publications

(82 reference statements)

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“…zero mean real Gaussian random variables with variance σ 2 w = 2πβT s , i.e., w i ∼ N R (0, σ 2 w ). In information-theoretic studies it is often assumed that the initial phase θ 0 is uniform in [0, 2π), i.e., θ 0 ∼ U [0, 2π), and then the process {θ i } is stationary [45].…”

Section: The Wiener Phase Noise Model In Communicationsmentioning

confidence: 99%

Phase Noise and Wideband Transmission in Massive MIMO

Pitarokoilis¹

2016

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In the last decades the world has experienced a massive growth in the demand for wireless services. The recent popularity of hand-held devices with data exchange capabilities over wireless networks, such as smartphones and tablets, increased the wireless data traffic even further. This trend is not expected to cease in the foreseeable future. In fact, it is expected to accelerate as everyday apparatus unrelated with data communications, such as vehicles or household devices, are foreseen to be equipped with wireless communication capabilities.Further, the next generation wireless networks should be designed such that they have increased spectral and energy efficiency, provide uniformly good service to all of the accommodated users and handle many more devices simultaneously. Massive multiple-input multiple-output (Massive MIMO) systems, also termed as large-scale MIMO, very large MIMO or full-dimension MIMO, have recently been proposed as a candidate technology for next generation wireless networks. In Massive MIMO, base stations (BSs) with a large number of antenna elements serve simultaneously only a few tens of single antenna, non-cooperative users. As the number of BS antennas grow large, the normalized channel vectors to the users become pairwise asymptotically orthogonal and, therefore, simple linear processing techniques are optimal. This is substantially different from the current design of contemporary cellular systems, where BSs are equipped with a few antennas and the optimal processing is complex. Consequently, the need for redesign of the communication protocols is apparent.The deployment of Massive MIMO requires the use of many inexpensive and, potentially, off-the-shelf hardware components. Such components are likely to be of low quality and to introduce distortions to the information signal. Hence, Massive MIMO must be robust against the distortions introduced by the hardware impairments. Among the most important hardware impairments is phase noise, which is introduced by local oscillators (LOs) v at the BS and the user terminals. Phase noise is a phenomenon of particular importance since it acts multiplicatively on the desired signal and rotates it by some random and unknown argument. Further, the promised gains of Massive MIMO can be reaped by coherent combination of estimated channel impulse responses at the BS antennas. Phase noise degrades the quality of the estimated channel impulse responses and impedes the coherent combination of the received waveforms.In this dissertation, wideband transmission schemes and the effect of phase noise on Massive MIMO are studied. First, the use of a low-complexity single-carrier precoding scheme for the broadcast channel is investigated when the number of BS antennas is much larger than the number of served users. A rigorous, closed-form lower bound on the achievable sum-rate is derived and a scaling law on the potential radiated energy savings is stated. Further, the performance of the proposed scheme is compared with a sumcapacity upper bound and ...

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Section: The Wiener Phase Noise Model In Communicationsmentioning

confidence: 99%

Phase Noise and Wideband Transmission in Massive MIMO

Pitarokoilis¹

2016

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“…The CBC algorithm, where the probability distribution of the hidden phase given the observation is modelled as a Tikhonov distribution 2 , is less complex than the trellis-based technique. In CBC, the incoming phase distribution is obtained by tracking the parameter of the Tikhonov distribution.…”

Section: Bit Mappingmentioning

confidence: 99%

“…Demodulation of signals affected by the phase noise is a classical and hot topic in the context of point-to-point radio backhauling systems [2], [3] and coherent optical systems [4]- [7]. In these systems, coded constellations with high spectral efficiency are adopted, and the performance of demodulation in the presence of phase noise becomes one of the major issues in the rush to higher and higher spectral efficiency.…”

Section: Introductionmentioning

confidence: 99%

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Bootstrapping Iterative Demodulation and Decoding Without Pilot Symbols

Pecorino

Mandelli

Barletta

et al. 2015

J. Lightwave Technol.

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Abstract-The iterative demodulation and decoding algorithm introduced in 2005 by Colavolpe, Barbieri, and Caire to cope with channels affected by phase noise needs pilot symbols to bootstrap. However, pilot symbols reduce the spectral efficiency of the system and, consequently, system's throughput. The aim of the paper is to show that trellis-based demodulation can be used to bootstrap the iterative process without the need of pilot symbols. Also, the complexity issue of trellis-based demodulation is addressed in the paper. The result is that the performance of iterative demodulation and decoding after the iterations is virtually unaffected by complexity reduction, provided that the reduced-complexity demodulator guarantees cycle-slip-free operation. From the numerical results presented in the paper we show that cycle-slip-free operation can be achieved with substantial complexity reduction also for phase noise associated with linewidths of practical interest.

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“…Moreover, phase noise has a higher impact on higher-level modulation schemes such as 64-QAM than lower level modulation schemes such as BPSK and ASK. Typical fixed-point broadband wireless applications such as Local Multipoint Distribution Service (LMDS), digital two-way microwave wireless service for the transmission of voice, video and data [3] are particularly effected by phase noise more than low frequency applications. This is because, typically these services uses frequencies above 20 GHz.…”

Section: Introductionmentioning

confidence: 99%

Combined amplitude and phase noise effects in QAM direct conversion receivers

Menon

Gunjegai

Aishwarya

et al. 2015

2015 International Conference on Microwave, Optical and Communication Engineering (ICMOCE)

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This paper deals with the modelling and simulation of combined phase and amplitude noise for QAM direct conversion receivers (DCR). We show that, due to phase noise, there is a cross coupling of quadrature component of the signal as well as quadrature component of amplitude noise to in-phase component of signal. Similarly, there is a cross coupling of inphase component of signal as well as in-phase component of amplitude noise to quadrature component of the signal. Based on the analysis, the symbol error rate (SER) for different levels of amplitude noise as well as phase noise values are presented for M-ary QAM modulation schemes. It is seen that for small phase noise, the SER approaches theoretical SER for only amplitude noise case and increases to large values for large phase noise.

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Capacity Bounds for MIMO Microwave Backhaul Links Affected by Phase Noise

Cited by 35 publications

References 30 publications

Phase Noise and Wideband Transmission in Massive MIMO

Phase Noise and Wideband Transmission in Massive MIMO

Bootstrapping Iterative Demodulation and Decoding Without Pilot Symbols

Combined amplitude and phase noise effects in QAM direct conversion receivers

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