Impact of Pilot Design on Achievable Data Rates in Multiple Antenna Multiuser TDD Systems

Samardžija, Dragan; Mandayam, Narayan B.

doi:10.1109/jsac.2007.070910

Cited by 16 publications

(6 citation statements)

References 35 publications

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“…The pilot signals are processed and an MMSE based channel estimate of the channel is formed. MMSE channel estimation is the commonly employed in multiuser MIMO systems [1], [4], [15]. Let Ψ jk ∈ C K×1 denote the training sequence of user k in cell j of duration K symbols.…”

Section: B Limitations In Gaining Channel Knowledgementioning

confidence: 99%

Uplink Linear Receivers for Multi-Cell Multiuser MIMO With Pilot Contamination: Large System Analysis

Kumarappan

Yates

Mandayam

2014

IEEE Trans. Wireless Commun.

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Abstract-Base stations with a large number of transmit antennas have the potential to serve a large number of users at high rates. However, the receiver processing in the uplink relies on channel estimates which are known to suffer from pilot interference. In this work, making use of the similarity of the uplink received signal in CDMA with that of a multi-cell multi-antenna system, we perform a large system analysis when the receiver employs an MMSE filter with a pilot contaminated estimate. We assume a Rayleigh fading channel with different received powers from users. We find the asymptotic Signal to Interference plus Noise Ratio (SINR) as the number of antennas and number of users per base station grow large while maintaining a fixed ratio. Through the SINR expression we explore the scenario where the number of users being served are comparable to the number of antennas at the base station. The SINR explicitly captures the effect of pilot contamination and is found to be the same as that employing a matched filter with a pilot contaminated estimate. We also find the exact expression for the interference suppression obtained using an MMSE filter which is an important factor when there are significant number of users in the system as compared to the number of antennas. In a typical set up, in terms of the five percentile SINR, the MMSE filter is shown to provide significant gains over matched filtering and is within 5 dB of MMSE filter with perfect channel estimate. Simulation results for achievable rates are close to large system limits for even a 10-antenna base station with 3 or more users per cell.

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Section: B Limitations In Gaining Channel Knowledgementioning

confidence: 99%

Uplink Linear Receivers for Multi-Cell Multiuser MIMO With Pilot Contamination: Large System Analysis

Kumarappan

Yates

Mandayam

2014

IEEE Trans. Wireless Commun.

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“…The duration of which is chosen to be less than channel coherence time (CT) to ensure that the channel remain constant over B symbols (usually B ranges from 10s to 100s of symbols depending on channel fading statistics [11][12]). Each frame is proceeded by a common pilot (CP) broadcasted from the BS at fixed times to all users.…”

Section: VImentioning

confidence: 99%

Hybrid multiple access coding with adaptive modulation

Aldroubi¹,

Ali

2013

2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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Multiple access communication techniques havedirect impact on bandwidth and power efficiencies for future wireless networks. In this paper, a new multiple access scheme combining both adaptive modulation and multiple access coding is proposed to provide an efficient and robust method of combining signals from multiple users over fading channels. Hybrid Multiple Access Coding with Adaptive Modulation (H-MACwAM) allows independent users to share a common link without subdivision in time, frequency, or code. Users adapt the phase and power of their signal independently according to their respective channels to ensure that their combined transmission belongs a predesigned composite constellation known at the receiver. The size and minimum distance of this constellation is varied using multiple access coding. The scheme offers higher rates than those available with conventional multiple access coding or superposition modulation. It was shown that large numbers of users can share a common link and achieve higher than unity rate without any degradation in BER performance.

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“…The first term in the denominator of (9) represents the error introduced by the imperfection of the channel estimate, the second term represents the residual interference (after LMMSE processing) that can be attributed to other users transmitting over the same PRB, and the third term is the thermal noise contribution. This SINR model to account for the effect of errors in channel estimation is similar to that of [15,16]. With NICE processing, the corresponding post-MMSE SINR may be expressed as…”

Section: A Sinr Computationmentioning

confidence: 99%

Uplink cooperation in wireless networks with NICE processing

Balachandran¹,

Kang²,

Karakayali³

et al. 2010

2010 IEEE Globecom Workshops

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There has been a lot of recent interest in the potential of inter-base station cooperation techniques to manage excessive out-of-cell interference in evolving cellular networks. In this paper, we propose and describe a signal processing approach based on a novel Network Interference Cancellation Engine (NICE), which opportunistically cancels dominant out-of-cell interference by exchanging decoded dominant interferer data among cooperating cells and reconstructing interfering signals. Simulation results with NICE processing in cellular networks show that substantial improvements in signal-to-interferenceplus-noise ratio may be achieved over current non-cooperative multi-antenna receiver processing techniques while allowing backhaul overhead to be reduced by approximately between one and two orders of magnitude relative to joint processing techniques employing the exchange of complex-valued received signal samples.

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Impact of Pilot Design on Achievable Data Rates in Multiple Antenna Multiuser TDD Systems

Cited by 16 publications

References 35 publications

Uplink Linear Receivers for Multi-Cell Multiuser MIMO With Pilot Contamination: Large System Analysis

Uplink Linear Receivers for Multi-Cell Multiuser MIMO With Pilot Contamination: Large System Analysis

Hybrid multiple access coding with adaptive modulation

Uplink cooperation in wireless networks with NICE processing

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