Asymptotic Analysis of LMMSE Multiuser Receivers for Multi-Signature Multicarrier CDMA in Rayleigh Fading

Peacock, M.J.M.; Collings, Iain B.; Honig, Michael L.

doi:10.1109/tcomm.2004.829519

Cited by 19 publications

(10 citation statements)

References 26 publications

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“…as was done in [22], and for more general channel distributions in [6 We note that neither of these techniques can be used to compute the output SINR for the MMSE receiver with isometric S, or the ALS receiver.…”

Section: Analysis Of Mmse Receivermentioning

confidence: 99%

Unified Large-System Analysis of MMSE and Adaptive Least Squares Receivers for a Class of Random Matrix Channels

Peacock

Collings

Honig³

2006

IEEE Trans. Inform. Theory

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We present a unified large system analysis of linear receivers for a class of random matrix channels.The technique unifies the analysis of both the minimum-mean-squared-error (MMSE) receiver and the adaptive least-squares (ALS) receiver, and also uses a common approach for both random i.i.d. and random orthogonal precoding. We derive expressions for the asymptotic signal-to-interference-plusnoise (SINR) of the MMSE receiver, and both the transient and steady-state SINR of the ALS receiver, trained using either i.i.d. data sequences or orthogonal training sequences. The results are in terms of key system parameters, and allow for arbitrary distributions of the power of each of the data streams and the eigenvalues of the channel correlation matrix. In the case of the ALS receiver, we allow a diagonal loading constant and an arbitrary data windowing function. For i.i.d. training sequences and no diagonal loading, we give a fundamental relationship between the transient/steady-state SINR of the ALS and the MMSE receivers. We demonstrate that for a particular ratio of receive to transmit dimensions and window shape, all channels which have the same MMSE SINR have an identical transient ALS SINR response. We demonstrate several applications of the results, including an optimization of information throughput with respect to training sequence length in coded block transmission.

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Section: Analysis Of Mmse Receivermentioning

confidence: 99%

Unified Large-System Analysis of MMSE and Adaptive Least Squares Receivers for a Class of Random Matrix Channels

Peacock

Collings

Honig³

2006

IEEE Trans. Inform. Theory

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“…channel entries having variance , i.e., . The equivalent transmit power constraint of transmitter equals (4) which grows with . This model will be used in the subsequent parts of this paper as it substantially facilitates the performed derivations.…”

Section: Equivalent Modified Channel and Transmit Power Models Formentioning

confidence: 99%

“…(4)] and the rate formula reads as A direct application of (12) implies that the achievable rate per stream converges to the large system rate per stream as : (14) where (15) which is the Shannon transform of evaluated at [cf. (7)].…”

Section: B Achievable Rates Under Equal Power Allocationmentioning

confidence: 99%

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Large System Analysis of Interference Alignment Achievable Rates for the MIMO Interference Channel

Bazzi

Dietl

Utschick

2015

IEEE Trans. Signal Process.

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In this paper, analytical rate expressions of interference alignment (IA) algorithms applied to the multiple-input multiple-output interference channel are derived in the large system limit. A large system analysis is performed by fixing the number of users and letting the number of transmit and receive antennas go to infinity at a finite fixed ratio. The asymptotic eigenvalue distribution of the direct channel gains resulting from IA algorithms is first obtained. Based on that, large system rate expressions under both water-filling power allocation and equal power allocation are derived in closed form. The obtained expressions are functions of the transmit power and noise power at the receivers and are independent of any other system parameters. Simulation results show that the achievable rates of different IA algorithms converge to the large system rates as the number of transmit and receive antennas increases, thereby showing that the large system expressions are valid for different IA variants. Simulation results also show that large system expressions provide accurate estimates of the average achievable rates for small and finite system parameters.Index Terms-Interference alignment, interference channels, large system analysis, random matrix theory.

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“…We have analyzed the performance of MC-CDMA in the presence of frequency-selective Rayleigh fading with multiple users, and multiple signatures per user in [11,26,28,32]. Our results apply in the large system limit as signatures and processing tend to infinity with fixed ratio, and enable the computation of performance measures as a function of system parameters such as data rates per user, noise level, and number of users.…”

Section: Multi-carrier Cdmamentioning

confidence: 99%

Adaptive Signal Processing Techniques for Robust, High Capacity Spread- Spectrum Multiple Access

Honig¹

2003

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Form Approve d O M B NO . 0704-0188Publ ic R e port ing burde n for t h is col l e ct ion of inform at ion is e s t im at e d t o ave rage 1 h our pe r re s pons e , incl uding t h e t im e for re vie w ing ins t ruct ions , s e arch ing e xis t ing dat a s ource s , gat h e ring and m aint aining t h e dat a ne e de d, and com pl e t ing and re vie w ing t h e col l e ct ion of inform at ion. Se nd com m e nt re garding t h is burde n e s t im at e s or any ot h e r as pe ct of t h is col l e ct ion of inform at ion, incl uding s ugge s t ions for re ducing t h is burde n, t o W as h ingt on H e adq uart e rs Se rvice s , D ire ct orat e for inform at ion O pe rat ions and R e port s , 1215 J e ffe rs on D avis H igh w ay, Suit e 1204, Arl ingt on, VA 22202-4302, and t o t h e O ffice of M anage m e nt and Budge t , Pape rw ork R e duct ion Proj e ct (0704-0188,) W as h ingt on, D C 20503.

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Asymptotic Analysis of LMMSE Multiuser Receivers for Multi-Signature Multicarrier CDMA in Rayleigh Fading

Cited by 19 publications

References 26 publications

Unified Large-System Analysis of MMSE and Adaptive Least Squares Receivers for a Class of Random Matrix Channels

Unified Large-System Analysis of MMSE and Adaptive Least Squares Receivers for a Class of Random Matrix Channels

Large System Analysis of Interference Alignment Achievable Rates for the MIMO Interference Channel

Adaptive Signal Processing Techniques for Robust, High Capacity Spread- Spectrum Multiple Access

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