MIMO OFDM receivers for Systems with IQ imbalances

Tarighat, A.; Sayed, Ali H.

doi:10.1109/tsp.2005.853148

Cited by 125 publications

(100 citation statements)

References 20 publications

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“…This chapter presents the concept of expanding the received signal sub-space to compensate for IQ mismatch at the frontend in spatial interference suppression systems. The idea has also been used to correct for IQ mismatch in MIMO-OFDM systems [28]. Section 3.1 presents the expanded subspace concept for mitigating IQ mismatch, Section 3.2 proposes an interference suppression architecture that is inspired by this idea and Section 3.3 presents simulation results demonstrating the additional interference suppression achievable through this architecture.…”

Section: Discussionmentioning

confidence: 99%

“…This suggests, on an intuitive level, that it might be possible to mitigate this effect if the signal and its conjugate are considered together, since this results in more information for the decoding process. Consider the following formulation for MIMO systems [28]. From Chapter 2, we have the following equations…”

Section: The Expanded Subspace Conceptmentioning

confidence: 99%

“…This is because in the presence of IQ mismatch the interference is not suppressed completely at the output of the frontend filter W, which might lead to poor estimation of the effective channelH or even worse the packet might not be detected at all. It is therefore essential to suppress the interference at the frontend completely even if we can compensate for IQ mismatch at the MIMO decoder by using the architecture proposed in [28].…”

Section: The Expanded Subspace Conceptmentioning

confidence: 99%

“…As noted in [28], the additional complexity associated with the expanded subspace concept is inverting a matrix with double the dimensions. The distorted signalz is filtered to producep, which is given by…”

Section: Architecture For Iq Mismatch Compensationmentioning

confidence: 99%

“…While several works in the literature have looked at performance degradation and compensation schemes for IQ mismatch in communication systems [23] - [28], the effect of IQ mismatch on Spatial Interference Suppression algorithms has not been investigated before. In this chapter, we show how IQ mismatch can limit the interference suppression ability of second order statistic based interference suppression algorithms.…”

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Addressing IQ mismatch in Spatial Interference Suppression systems

Pereira

Daneshrad

2012

MILCOM 2012 - 2012 IEEE Military Communications Conference

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Professor Babak Daneshrad, ChairSecond order statistic based Spatial Interference Suppression has been shown effective in suppressing strong interference from jammers or concurrent transmissions. Interference suppression abilities are especially useful to commercial systems that need to support an ever increasing number of wireless devices in the shared wireless medium, and military systems that need to communicate in the presence of strong jammers. However, implementation impairments in the RF frontend can be a major impediment to the design of such systems since the interference can be several orders of magnitude stronger than the signal.The main contribution of this thesis is to analyze the impact of implementation impairments, in particular IQ mismatch, and to compensate for it in interference suppression systems. Investigating the factors that limit the interference suppression ability of such systems is important, as this might lead to answers about the bounds on jammer suppression or concurrent links supportable in practical communication systems. Moreover, it is important to mitigate these limits on interference suppression as we push for denser networks and more jammer resistance. This work presents architectures for IQ mismatch compensation in both narrowband and wideband interference suppression systems.Chapter 1 presents an overview of Spatial Interference Suppression algorithms. The mechanism behind interference suppression based on second order statistics of the interference is ii illustrated, and the use of spatial interference suppression as frontend filters for packet based communication systems is also discussed.Chapter 2 discusses implementation impairments in spatial interference suppression systems.It is shown that IQ mismatch is a key limiter to the interference suppression ability of spatial interference suppression algorithms that are based on the second order statistics of the interference.Chapter 3 presents the expanded sub-space concept, and shows how IQ mismatch in spatial interference suppression systems can be compensated for in the expanded sub-space. An interference suppression architecture for narrowband systems with flat fading channels is introduced, and simulation results are presented that show that the effect of IQ mismatch can be mitigated.Chapter 4 extends the interference suppression architecture with IQ mismatch compensation to wideband systems with frequency selective channels. An architecture based on sub-banding is proposed that utilizes the existing blocks from wideband interference suppression systems.Simulation results in scenarios typical of indoor environments are presented to indicate the expected gains in a practical system.Chapter 5 concludes the thesis, with a brief discussion on how the expanded sub-space concept can be used to mitigate the frequency selectivity of the channel.

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Section: Discussionmentioning

confidence: 99%

Section: The Expanded Subspace Conceptmentioning

confidence: 99%

Section: The Expanded Subspace Conceptmentioning

confidence: 99%

Section: Architecture For Iq Mismatch Compensationmentioning

confidence: 99%

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