 Research
 Open Access
Green radio despite "Dirty RF" frontend
 Myriam Ariaudo^{1}Email author,
 Inbar Fijalkow^{1},
 JeanLuc Gautier^{1},
 Mathilde Brandon^{1, 2},
 Babar Aziz^{1} and
 Borislav Milevsky^{1}
https://doi.org/10.1186/168714992012146
© Ariaudo et al; licensee Springer. 2012
Received: 30 September 2011
Accepted: 18 April 2012
Published: 18 April 2012
Abstract
In this article, we show that the nonideal RadioFrequency (RF) frontends have to be corrected in order to contribute in a Green radio development. In fact, the effects of typical RF imperfections, like nonlinearities, carrier frequency offsets, and IQ imbalances, can be compensated for, when digital correction algorithms are applied. Such algorithms enable Green applications (e.g., Orthogonal Frequency Division Multiple Access for the uplink) despite a restrictive RF imperfection, or allow a less constrained hardware design, which reduces the chip area and the number of components (Green design) or facilitate the reduction of spectral pollution and of power consumption (Green transmission). So, we propose to implement these correction methods to compensate for the damaging effects of RF imperfections in mind of a Green issue.
Keywords
 communication electronic systems and components
 interference reduction
 RF imperfections compensation
 RF nonlinearity
 carrier frequency offset
 agile multiband synthesizer
Introduction
It is now well established that the optimization of the performance of the whole communication system has to consider the effect of its RadioFrequency (RF) frontend to avoid a waste of resources and a huge margin in design. This requirement becomes particularly important due to the increasing use of complex dynamic signals, like Orthogonal Frequency Division Multiplexing (OFDM). Such signals are necessary to improve the system performance in hostile environment or to develop reconfigurable systems for cognitive radio. Concerning the RF part, designing a Green radio first consists in the improvement of efficiency. It is well known that the most powerconsuming circuit is the power amplifier (PA) of the transmitter of handset systems as well as of the base station [1]. Many authors have considered this issue in particular since complex modulations with nonconstant envelope signals are employed.
On top of that, the RF frontend limits the performance of the transmission because of its imperfections. Indeed the performance is affected by various RF imperfections like nonlinearities, frequency offset between the transmitter and the receiver, phase noise of local oscillator, IQ imbalance, etc. These RF imperfections and their impacts have been reported in a new concept referred as "Dirty RF" by Fettweis et al. [2]. In recent years, several parts of the RF frontend have been considered to evaluate the overall performance of a communication system, and digital methods have been developed to compensate for their damaging effects and then to improve the performance of a given nonideal system.
In this article, we show how the correction of RF frontend imperfections can participate in the design of Green radio. Some of these corrections enable a Green transmission (in the sense of the reduction of spectral pollution and energy consumption) or a Green application (like Orthogonal Frequency Division Multiple AccessOFDMA in the uplink); other corrections allow to reduce the chip area and the number of circuit components, and thus allow a Green production. So, in the sequel, we give some examples to show that the application of our correction methods can help in the compensation of the effect of RF circuit imperfections in different Green objectives.
Green radio despite "Dirty RF physical implementation" thanks to digital correction
One Green objective for the RF frontend can be to minimize the chip area and the number of components. To achieve this objective, a transmission system with direct frequency conversion is a good solution. Unfortunately, such systems are more sensitive to some RF imperfections, like IQ imbalance in the modulator/demodulator or carrier frequency offsets (CFOs) (due to a higher frequency of the local oscillator). The consequences are a degradation of the performance, which has to be compensated for.
It is well known that the IQ imbalance can be modeled by a mismatch of the phase φ due to an imprecise phase quadrature and/or by a mismatch of the gain g due to different mixer characteristics between the two branches I and Q.
where F_{ eIk }and F_{ eQk }are the I and Q frequency responses on the band, k is the carrier index (particularly in the case of an OFDM signal), n is the symbol index, and E_{ k }(n) is the initial symbol to be transmitted. The gain of the PA is considered to be linear and equal to 1 in this equation.
The IQ imbalance causes interference between the two branches. Furthermore, the received signal is affected by the propagation channel and the receiver noise. A similar model takes into account the IQ imbalance at the receiver.
In order to compensate for these degradations, the receiver needs to jointly estimate the channel response and the imbalance characteristics before correcting the received symbols.

an IQ imbalance at the transmitter up to 10° in phase and 20% in gain with a degradation of the SignaltoNoise ratio (SNR) less than 2 dB for a fixed uncoded BER of 10^{2};

an IQ imbalance at the receiver up to 30° in phase and 100% in gain with a degradation of the SNR less than 1.5 dB for a fixed uncoded BER of 10^{2}.
This example shows that it is then possible to relax constraints on the implementation because the phase variation induces a possible variation of the branches length, leading to a reduction of the chip area. For a carrier frequency in the GHz range, a phase of several degrees corresponds to a length of several millimeters.
The ability of efficiently correcting the effect of the IQ imbalance (frequency selective or not) facilitates to accept an imperfect physical implementation with a reduced chip area. That is a way to help in the design of a Green radio especially in the case of a directconversion system.
Green radio despite "Dirty RF amplifier" thanks to channels pollution reduction method
One Green objective for the RF frontend is to minimize the spectral pollution of adjacent channels.
At the same time, it is necessary to optimize the transmitter efficiency, for the base station as well as handsets. To benefit from a large PA efficiency, it is necessary to operate near the nonlinear zone, degrading consequently the linearity of the whole system. This brings a particular disadvantage for nonconstant envelope signals. It is then necessary to compensate for that by applying a linearization method or a signal dynamic reduction to avoid the pollution of neighboring channels.
Though many studies have dealt with this issue, applying such techniques separately is not sufficient, in particular in the case of complex signals like OFDM, which present a large dynamic. The combination of these methods seems promising [4] as long as the complexity is not dramatically increased.
The ACE method is well suited, as it is dedicated to OFDM signals. Moreover, compared to other methods, it allows to improve the outofband performance without degrading the inband performance. The ACE method makes it possible to modify the constellation of the digital modulation of OFDM symbols to reduce their dynamic without degrading the BER. The ACE is an iterative process, which requires one extra FFT algorithm. However, the development of the digital circuits allows the implementation of the ACE with increasing efficiency [6].
The DPD of the input signal by a function that approximates the inverse of the nonlinearity is the most popular linearization method. In our case, the "predistortion function" is determined based on the amplifier output (path 1 in Figure 2), and it is modeled using a memory polynomial expression. As this algorithm computes directly the predistorter characteristic, it is less complex than those that need to evaluate the amplifier characteristic before inverting it.
The predistortion function is then applied to the OFDM signal, of which the PAPR has been reduced. This predistorded OFDM signal is supposed to be nearly linearly amplified when passing through the amplifier (path 2 in Figure 2).
These new measurement results confirm an improvement of the linearity performance, compared to the cases where the two methods are applied separately, in the immediate adjacent channels as well as in the next ones. Indeed better ACPR and AltCPR performances are obtained when ACE and DPD are jointly applied (red curve). For example, for an output power of 42 dBm, the ACPR is improved by 17 dB compared to the initial case (without ACE and DPD) and the AltCPR is improved by 12 dB. Moreover, for a target ACPR, the work point can be pushed near the saturation zone of the amplifier to achieve a better efficiency. These results are obtained in a more sensitive case (16QAMOFDM) than in [5] (QPSKOFDM) proving the robustness of our method.
So, we showed that the combination of these two methods allows to reduce the pollution of both the adjacent and the following channels and thus it helps in the deployment of Green radio systems. Indeed, not only the transmitter efficiency of the considered user is improved, but also the adjacent users are less interfered. Furthermore, BER measurements have shown negligible degradations after the application of the predistortion and ACE methods.
Green radio despite "Dirty RF synthesizer" thanks to interferences reduction method
Another Green objective of new communication systems is to be flexible. However, band and subband flexibility leads to an increase of the sensibility to the RF imperfections or to complex RF frontends. In the following, we show two examples for the case where interference reduction methods permit to deploy efficient Green systems due to the reduction of the effect of various RF imperfections of the frequency synthesizer.
OFDMA in uplink systems for Green radio
where f_{c} is the carrier frequency, $\delta {f}_{\mathsf{\text{c}}}^{\left(u\right)}$ represents the CFO of user u with respect to f_{ c }, p^{(}^{ u }^{)} is the impulse response of the filter at the transmitter, T is the symbol period of an OFDMA symbol, N_{ p }is the total number of subcarriers, and ${{a}_{k}}^{\left(u\right)}$ are the symbols after the output of the inverse DFT.
with H ( u ), the diagonal DFT channel matrix for a user u, δ^{ (u) } , a diagonal matrix of the shift coefficients ${\delta}^{{k}^{(u)}}={e}^{\frac{{j2\pi k\delta {f}_{\text{c}}^{(u)}T}^{}}{{N}_{p}}}$ due to the CFO $\delta {f}_{\mathsf{\text{c}}}^{\left(u\right)},{h}_{\mathrm{\Delta}}\left(u\right)$, a triangular matrix involving the channel impulse response due to the effect of the CFO on the cyclic prefix (this term is usually neglected in the literature).
As opposed to other models, like [9], our model of the received signal takes into account the effect of the CFO on the cyclic prefix. This makes the model more realistic and improves the channel estimation [10].
The BER performance is improved due to the selfSIC method, which reduces the interference at the receiver. Up to a normalized CFO of 0.3, the BER of 10^{2} is practically maintained. A normalized CFO of δf^{(u)}= 0.3 corresponds in this example to ± 20 ppm stability at 5 GHz; this range of δf^{(u)}corresponds to realistic characteristics of an actual VCO.
Various simulated cases show that the quality of improvement does not depend on the blocksize used for each user. This makes our algorithm very competitive in terms of complexity compared to other methods. As an example, the interference cancellation method described in [11] depends on the blocksize K and as a consequence its complexity increases with the blocksize. Indeed, large blocksizes K × K require the implementation of the inversion of large G^{(u)}matrices. Table 1 compares the computational complexity of our proposed selfSIC method to that of the interference cancellation method proposed in [11].
It is clear that our proposed selfSIC overcomes the disadvantage of large matrix inversions, especially when the number of subcarriers in the block is large.
So, we prove that despite a mismatch in the lowcost RF frontend synthesizers, it is possible to deploy OFDMA in an uplink transmission due to a not so costly digital correction. This dirty RF model and new digital correction is a suggestion for a Green flexible system.
Optimized multiband synthesizer for Green radio
In the context of modern Green communications, it is important to allow frequency band hoping to benefit from frequency diversity for each user or from multimode running. However, the required frequency synthesizer can suffer from high complexity, as it needs to fulfill the constraints necessary to avoid interference between the users. Based on the example of the MBOFDM (multiband OFDM) standard [12] with very strict constraints, we have studied and developed an agile frequency synthesizer, able to switch between 14 frequency bands between 3.432 and 10.296 GHz [13]. It requires only one phase locked loop (PLL); the frequencies are generated by consecutive mixing and selection between different outputs of the PLL.
Difference between the power of the main frequency and the total spurs power in dBc (has to be greater than 24 dBc)
Frequency (MHz)  Without bandpass filter  With bandpass filter  

Channel I  Channel Q  Channel I  Channel Q  
8184  18.331  19.031  24.3  27.7 
8712  18.745  17.879  24.1  27.1 
9240  19.446  18.634  31.8  31.8 
9768  17.457  16.673  29.6  25.9 
10296  17.839  16.696  27.6  24.4 
However, the system can be optimized in terms of the surface area and the number of components if a compensation algorithm is applied to reduce the interference at the receiver produced by the spurs. We have shown, in an uplink transmission, that a SIC algorithm applied at the receiver can improve the performance [14]. With the developed method, it is possible to tolerate a level between total spurious power and the generated frequency of 17 dBc (instead of 24 dBc) with a degradation of the SNR less than 0.1 dB. As shown in Table 2, this minimum level is not reached without a filter, except for the channel Q of 9768 and 10296 MHz, for which the level is nevertheless very close to 17 dBc.
This result shows that the filters may be removed because the associated degradation can be compensated for. The BER at the receiver will not be increased due to the reduction of the induced interferences.
In such a complex structure, removing the filters is an efficient way to reduce the RF system complexity and to optimize the chip surface with regard to a Green objective for the uplink transmission.
Conclusion
Though the RF frontend has often been considered as a degrading part of the system because of its "dirty" characteristics, it has to be taken into account in the development of a Green radio: the imperfections of RF frontend can either be minimized, or they can be compensated for. The examples presented in this article prove that it is possible to tolerate RF imperfections, as the performance can greatly be improved by digital correction methods. This leads to either more efficient transmission in terms of power consumption or spectral pollution, or to a smaller and less complex radio frontend. Both approaches contribute to a Green radio.
Declarations
Acknowledgement
The authors would like to thank Jessica Bouvier and Sylvain Traverso of THALES Communications for their participation in the amplifier predistortion study, and the French Ile de France Region DIM for supporting the study on OFDMA uplink through the DESAP project.
Authors’ Affiliations
References
 Correia LM, Zeller D, Blume O, Ferling D, Jading Y, Godor I, Auer G, Van de Perre L: Challenges and enabling technologies for energy aware mobile radio networks. IEEE Commun Mag 2010, 48(11):6672.View ArticleGoogle Scholar
 Fettweis G, Lôhning M, Petrovic D, Windisch M, Zillmann P, Rave W, Dirty RF: a new paradigm. Int J Wirel Inf Netw 2007, 14(2):133148.View ArticleGoogle Scholar
 Traverso S, Ariaudo M, Fijalkow I, Gautier JL, Lereau C: Decision directed channel estimation and high I/Q imbalance compensation in OFDM receivers. IEEE Trans Commun 2009, 57(5):12461249.View ArticleGoogle Scholar
 Bo A, Zhixing Y, Changyong P, Taotao Z, Jianhua G: Effects of PAPR reduction on HPA predistortion. IEEE Trans Consum Electron 2005, 51(4):11431147.View ArticleGoogle Scholar
 Brandon M, Ariaudo M, Traverso S, Bouvier J, Fijalkow I, Gautier JL: Linearity improvement thanks to the association of active constellation extension and digital predistortion for OFDM. In Proceedings of IEEE NEWCAS. Bordeaux; 2011:293296.Google Scholar
 Chen S, Yu C, Tsai C, Tang J: A new IFFT/FFT hardware implementation structure for OFDM applications. IEEE AsiaPacific Conference on Circuit and Systems, Taiwan 2004, 10931096.Google Scholar
 Galda D, Gruenheid R, Rohling H: OFDM: a flexible and adaptive air interface for a 4G mobile communication system. In International Conference on Telecommunications (ICT). Beijing; 2002:514.Google Scholar
 Aziz B, Fijalkow I, Ariaudo M: Intercarrier interference in uplink OFDMA systems with carrier frequency offset. In PIMRC. Istanbul; 2010:476751.Google Scholar
 Cao Z, Tureli U, Yao YD, Honan P: Frequency synchronization for generalized OFDMA uplink. In Proceedings of Globecom'2004 IEEE. Volume 2. Dallas; 2004:10711075.Google Scholar
 Aziz B, Fijalkow I, Ariaudo M: Joint estimation of channel and carrier frequency offset from the emitter, in an uplink OFDMA system". In ICASSP. Prague; 2011:34923495.Google Scholar
 Yucek T, Arslan H: Carrier frequency offset compensation with successive cancellation in uplink ofdma systems. IEEE Trans Wirel Commun 2007, 6(10):35463551 .View ArticleGoogle Scholar
 Mishra C, ValdesGarcia A, Bahmani F, Batra A, SanchezSinencio E, SilvaMartinez J: Frequency planning and synthesizer architectures for multiband UWB radios. IEEE Trans Microwave Theory Tech 2005, 53(12):37443756.View ArticleGoogle Scholar
 Traverso S, Ariaudo M, Gautier JL, Lereau C, Fijalkow I: A 14band low complexity and high performance synthesizer architecture for MBOFDM communication. IEEE Trans Circ Syst II 2007, 54(6):552557.View ArticleGoogle Scholar
 Milevsky B, Ariaudo M, Gautier JL, Fijalkow I, Hristov M: Successive interference cancellation (SIC) in MBOFDM receiver with imperfect local oscillator. In EuMC. Paris; 2010:385388.Google Scholar
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