On the Capacity of MIMO-OFDM Systems with Doubly Correlated Channels

Shen, Guoliang; Liu, Shouyin; Jang, Seong-Hyun; Chong, Jong‐Wha

doi:10.1109/vetecf.2007.262

Cited by 4 publications

(5 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The MI for multiple user MIMO-OFDM systems can be obtained from MI of a single user in a MIMO-OFDM system by modifying Equation (3) of [20]. It is assumed that transmitter has no CSI, and the receiver has perfect CSI.…”

Section: Performance Analysis Of Ol and CL Systemsmentioning

confidence: 99%

“…For N t transmit antennas with equal transmit power and N r receive antennas, the generalised capacity expression

C = {log}_{2} det (][, I + \frac{ρ}{N_{t}})

where I is an N r × N r identity matrix, H is a N t × N r matrix, H † is its transpose conjugate (Hermitian) and ρ is the average SNR. The MI for multiple user MIMO‐OFDM systems can be obtained from MI of a single user in a MIMO‐OFDM system by modifying Equation (3) of [20]. It is assumed that transmitter has no CSI, and the receiver has perfect CSI.…”

Section: Performance Analysis Of Ol and CL Systemsmentioning

confidence: 99%

“…This channel correlation which degrades the capacity depends on the physical parameters of the MIMO system and the scatter characteristics. The physical parameters include antenna arrangement and spacing, the angle spread, the angle of arrival etc [20].…”

Section: Performance Analysis Of Ol and CL Systemsmentioning

confidence: 99%

“…The correlation at the transmitter means channel coefficients from different transmit antennas to a single receiver antenna are correlated. Similarly, correlation at the receive antenna means channel coefficients from different receive antennas to a single transmit antenna are correlated [20].…”

Section: Performance Analysis Of Ol and CL Systemsmentioning

confidence: 99%

See 3 more Smart Citations

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

View full text Add to dashboard Cite

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.

show abstract

Section: Performance Analysis Of Ol and CL Systemsmentioning

confidence: 99%

“…For N t transmit antennas with equal transmit power and N r receive antennas, the generalised capacity expression

C = {log}_{2} det (][, I + \frac{ρ}{N_{t}})

Section: Performance Analysis Of Ol and CL Systemsmentioning

confidence: 99%

Section: Performance Analysis Of Ol and CL Systemsmentioning

confidence: 99%

Section: Performance Analysis Of Ol and CL Systemsmentioning

confidence: 99%

See 2 more Smart Citations

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

View full text Add to dashboard Cite

show abstract

“…And So, equation (6) So according to conference [5], [8], [9] , and equation (7), as suppose in [5] , we ignored the loss in spectral efficiency due to the CP, we can write the mutual information of MIMO-OFDM system under average power: …”

Section: Recieve Signal Modelsmentioning

confidence: 99%

Effect of Channel Estimation Error on MIMO-OFDM Systems Capacity

Wang

2010

2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM)

View full text Add to dashboard Cite

Capacity of MIMO-OFDM system with channel estimation error was researched. Based on SVD, factors about channel estimation error percent and the number of multi-path were analyzed. The Monte-Carlo simulations present that capacity of MIMO-OFDM system would decrease obviously as channel estimation error increasing in large SNR; it would loss almost half capacity when estimation error ups to 10%. Keywords-channel estimation error;multi-path fadin gchannel; SVD;MIMO-OFDMI.

show abstract

WITHDRAWN: Capacity of single user MIMO-OFDM systems with doubly-correlated channels under various fading distributions

Shyamala

Bhaskar

2011

Digital Signal Processing

View full text Add to dashboard Cite

On the Capacity of MIMO-OFDM Systems with Doubly Correlated Channels

Cited by 4 publications

References 15 publications

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

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

Effect of Channel Estimation Error on MIMO-OFDM Systems Capacity

WITHDRAWN: Capacity of single user MIMO-OFDM systems with doubly-correlated channels under various fading distributions

Contact Info

Product

Resources

About