Advances in MIMO Techniques for Mobile Communications—A Survey

Khalid, Farhan; Speidel, Joachim

doi:10.4236/ijcns.2010.33031

Cited by 20 publications

(9 citation statements)

References 35 publications

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“…Further, we apply Rayleigh and Rician channel coefficients for the channel matrix H using (19). For the Rayleigh case, H LOS is a zero matrix.…”

Section: Extension Of the Analysis To Incorporate Rayleigh/ Rician Chmentioning

confidence: 99%

“…A detailed review of various MU-MIMO uplink and downlink techniques clarifying the underlying concepts and emphasising the importance of MU-MIMO in cellular communication techniques and the promising convex optimisation approaches to MIMO system design was discussed in [19].…”

Section: Iet Communicationsmentioning

confidence: 99%

“…Step 11: Using (19), the expression for the channel matrix, H, is computed for Rayleigh and/or Rician fading channels. Further, the expressions for correlation matrices computed at the transmitter and receiver side, ∑ T and ∑ R , respectively, can be utilised to design a channel matrix, H w , which takes into account the correlation at the transmitter and/or receiver side.…”

Section: Performance Analysis Of Ol and CL Systemsmentioning

confidence: 99%

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Performance modelling of open loop and closed loop multiuser multiple‐input multiple‐output‐orthogonal frequency division multiplexing systems through channel analysis

Bhaskar

John

2015

IET Communications

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Multiple-input multiple-output (MIMO) technology can be combined with orthogonal frequency division multiplexing to achieve diversity gain and improvement in system spectrum efficiency. The relative capacity of different system configurations are obtained using various channel characteristics. In this study, the probability density function (PDF) and the cumulative distribution function expressions of the condition number [i.e. the maximum to minimum singular value ratio (MMSVR)] of the channel state information matrix are derived. This ratio is directly related to noise enhancement in open loop (OL) multiuser MIMO systems. The probability density function (PDF) of MMSVR is directly used to compute the channel capacity if specific channels fail at high throughput. Capacity expressions in terms of MMSVR are derived for OL and closed loop (CL) multiuser MIMO systems. The capacity of both OL and CL systems are plotted for different system specifications, different fading channels and compared with each other under both semi and doubly correlated channels. A novel algorithm is developed to compute the channel capacity and PDF of MMSVR of a generic N T × N R MIMO system.

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“…Further, we apply Rayleigh and Rician channel coefficients for the channel matrix H using (19). For the Rayleigh case, H LOS is a zero matrix.…”

Section: Extension Of the Analysis To Incorporate Rayleigh/ Rician Chmentioning

confidence: 99%

Section: Iet Communicationsmentioning

confidence: 99%

Section: Performance Analysis Of Ol and CL Systemsmentioning

confidence: 99%

See 1 more Smart Citation

Performance modelling of open loop and closed loop multiuser multiple‐input multiple‐output‐orthogonal frequency division multiplexing systems through channel analysis

Bhaskar

John

2015

IET Communications

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“…This promising additional gain achieved by using Multiple Input Multiple Output (MIMO) technology has rejuvenated the field of wireless communication. Nowadays this technology is integrated into all recent wireless standards such as IEEE 802.11n, IEEE 802.16e and LTE [5,6]. The main objective of this chapter is to provide a comprehensive overview of various MIMO Techniques and critical discussion on the recent advances in Multi-user MIMO precoding design and pointing to a new era of the precoding application in WiMAX systems.…”

Section: Introductionmentioning

confidence: 99%

On MU-MIMO Precoding Techniques for WiMAX

Saeid¹,

Jeoti²,

Samir³

2013

Selected Topics in WiMAX

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Additional information is available at the end of the chapter http://dx.doi.org/10.5772/56034 . IntroductionFuture wireless communication systems will require reliable and spectrally efficient transmission techniques to support the emerging high-data-rate applications. The design of these systems necessitates the integration of various recent research outcomes of wireless communication disciplines. So far, the most recent tracks of investigations for the design of the spectrally efficient system are multiple antennas, cooperative networking, adaptive modulation and coding, advanced relaying and cross layer design. [ , ]. The main objective of this chapter is to provide a comprehensive overview of various MIMO Techniques and critical discussion on the recent advances in Multi-user MIMO precoding design and pointing to a new era of the precoding application in WiMAX systems.The chapter opens with the basic preliminaries on MIMO channel characterization and MIMO gains in section . This is followed by theoretical overview of precoding for MU-MIMO channel in section . Section describes a new precoding method and numerical simulation stressing the importance of the proposed precoding in the WiMAX context. Section concludes the chapter.

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“…The true channel matrix, which the transmitter does not fully know, can modeled as a Gaussian random matrix (or vector) who's mean and covariance is given in the feedback [16]. In this case of action , MIMO system capacity can be improved based on using water filling principle, through assigning different levels of transmit power to various transmitting antennas [17].…”

Section: Perfect Csi At the Transmittermentioning

confidence: 99%