Carrier Frequency Offset in Coordinated Multibase MIMO Narrowband Systems

Zarikoff, Brad; Cavers, J.K.

doi:10.1109/vetecs.2008.189

Cited by 11 publications

(5 citation statements)

References 12 publications

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“…The output of the matched filter contains sufficient statistics at one sample per symbol, given that the influence of the CFO over the signaling pulse duration is negligible. The signal as observed at the receiver is affected by multiple CFOs; the reason for these CFOs can be attributed to either an independent Doppler effect on each multi-path [6] or to independent local oscillators (LOs) at each transmit antenna array [5].…”

Section: A System Modelmentioning

confidence: 99%

“…As presented in [5], the progressive phase rotations represented by the D matrix can be understood as a perturbation on the channel state that degrades the orthogonality of the transmit and receive filters. This provides motivation for finding a high accuracy CFO estimate.…”

Section: B Carrier Frequency Offsetmentioning

confidence: 99%

“…For CMB-MIMO, the carrier frequency offset (CFO) between each basestation (BS) is capable of disrupting the virtual channels. For example, if the downlink of a CMB-MIMO system relies on spatial zero forcing (ZF) to separate signals to different users, degraded CSI resulting from CFO can cause some loss of orthogonality, and therefore increased interference and reduced capacity [5].…”

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confidence: 99%

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Multiple Carrier Frequency Offset and Channel State Estimation in the Fading Channel

Zarikoff

Cavers

2008

2008 IEEE 68th Vehicular Technology Conference

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Abstract-The joint estimation of multiple carrier frequency offsets (CFOs) and channel state information (CSI) in a multibase MIMO downlink system is considered here for the case of a fading channel. The multiple CFOs result from independent local oscillators at each basestation (BS), and cause accumulation of phase errors that compromise beamforming accuracy. Using previously devised multiple CFO estimation techniques for simultaneously transmitted training sequences in a non-fading channel, we begin by examining the effects of fading on a linear channel state estimate. An example illustrates that a fade rate threshold can be defined after which linear channel estimation is infeasible. Because of the dependence of the CFO estimators on the CSI estimate, this threshold applies to the CFO estimates as well. As a way to combat the channel variation, the maximum likelihood metric is modified to accommodate a parameterized fading channel estimate.I. INTRODUCTION To achieve a high-capacity multiuser MIMO system, channel state information (CSI) is the most powerful tool available to the communications engineer. With high quality CSI, the inherent diversity of the multipath in the system can be used to create virtual channels that are independent of one another. These channels can be used as a means to eliminate inter-user interference without having to resort to time and/or frequency expansion. If the channel state is static, then these virtual channels can be created once and used indefinitely; for fading channels, periodic channel estimation is necessary for update purposes. The virtual channels are very sensitive to errors in the CSI, as demonstrated in [1].As a means to increase system capacity further, coordinated multibase MIMO (CMB-MIMO) systems, as proposed in [2], [3], [4], share information in order to create a single, very large MIMO system. For CMB-MIMO, the carrier frequency offset (CFO) between each basestation (BS) is capable of disrupting the virtual channels. For example, if the downlink of a CMB-MIMO system relies on spatial zero forcing (ZF) to separate signals to different users, degraded CSI resulting from CFO can cause some loss of orthogonality, and therefore increased interference and reduced capacity [5].For BS frequency accuracy of, for example, ε 0 = 1 ppm, and a static or slowly time-varying channel, it is the CFOs that

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Section: A System Modelmentioning

confidence: 99%

Section: B Carrier Frequency Offsetmentioning

confidence: 99%

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confidence: 99%

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Multiple Carrier Frequency Offset and Channel State Estimation in the Fading Channel

Zarikoff

Cavers

2008

2008 IEEE 68th Vehicular Technology Conference

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“…Channel errors can be caused by channel estimation, feedback quantization, feedback delay as well as by time and frequency synchronization misalignments among the oscillators of the cooperative base stations. In [7] the estimation of multiple frequency offsets is investigated. The required frequency accuracy has been studied in [8].…”

Section: Introductionmentioning

confidence: 99%

Impairment modeling for joint transmission CoMP

Manolakis

Thiele

Oberli

et al. 2011

2011 2nd International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace &Amp; Elect

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Base station coordination is envisioned as a key technology in future mobile networks. It reduces the interference between adjacent cells and promises enhancement of spectral efficiency. However, little is known about the penalties due to impairments. Channel errors may be caused by channel estimation, feedback delay as well as by synchronization errors among the base stations. Hence, the computation of the precoder relies on imprecise information and the orthogonality between the user data is disturbed. In this paper, we give an overview on potential impairment effects. We derive an accurate signal model capturing the effect of synchronization impairments depending on the feedback delay. The resulting interference levels must not be larger than the one obtained after cooperation of the base stations in the cluster being limited by interference of non-coordinated base stations surrounding the cluster. We introduce an equivalent mean square error for these impairment eff ects, propose a practical way to evaluate the corresponding performance degradation and discuss compensation mechanisms

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“…In addition, simulation results exist on the impacts of CFO in cooperative multiuser MIMO systems [19]. Zarikoff also shows that in multiuser systems the CFOs degrade the accuracy of the beamformer, hence decreasing the capacity [20]. Mudumbai et al, consider a cluster of single-antenna sensor nodes communicating with a distant receiver, where the sensor nodes share a consistent carrier signal [12].…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of distributed ZF beamforming in the presence of CFO

Lebrun

Zhao

Pollin

et al. 2011

J Wireless Com Network

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We study the effects of residual carrier frequency offset (CFO) on the performance of the distributed zero-forcing (ZF) beamformer. Coordinated transmissions, where multiple cells cooperate to simultaneously transmit toward one or multiple receivers, have gained much attention as a means to provide the spectral efficiency and data rate targeted by emerging standards. Such schemes exploit multiple transmitters to create a virtual array of antennas to mitigate the co-channel interference and provide the gains of multi-antenna systems. Here, we focus on a distributed scenario where the transmit nodes share the same data but have only the local knowledge of the channels. Considering the distributed nature of such schemes, time/frequency synchronization among the cooperating transmitters is required to guarantee good performance. However, due to the Doppler effect and the non-idealities inherent to the local oscillator embedded in each wireless transceiver, the carrier frequency at each transmitter deviates from the desired one. Even when the transmitters perform frequency synchronization before transmission, a residual CFO is to be expected that degrades the performance of the system due to the in-phase misalignment of the incoming streams. This paper presents the losses of the signal-to-noise ratio gain analytically and the diversity order semi-numerically of the distributed ZF beamformer for the ideal case and in the presence of a residual CFO. We illustrate our results and their accuracy through simulations.

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Carrier Frequency Offset in Coordinated Multibase MIMO Narrowband Systems

Cited by 11 publications

References 12 publications

Multiple Carrier Frequency Offset and Channel State Estimation in the Fading Channel

Multiple Carrier Frequency Offset and Channel State Estimation in the Fading Channel

Impairment modeling for joint transmission CoMP

Performance analysis of distributed ZF beamforming in the presence of CFO

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