Marvell International Limited

Ping Gao

Hongyuan Zhang

Rohit U Nabar

Sudhir Srinivasa

Xiayu Zheng

Atul Salhotra

Bo Wang

Swaroop Venkatesh

Sergey Timofeev

Lokesh Sundaramurthy Satrasala

Manikandan Chandrasekar

In accordance with embodiments of the present disclosure there is provided a method for carrier sensing. The method includes receiving, at a wireless receiver, an input signal, and generating, based on a sampling period, a plurality of data samples from the input signal. The method further includes periodically combining a first data sample from the plurality of data samples with a second data sample that is one or more sampling periods before the first data sample to generate a combined data sample. The method further includes generating an auto-correlated output for carrier sensing based on the combined data sample. The auto-correlated output is provided to generate an estimate of phase difference between the first sample and the second sample for the periodic combining.

Systems and methods for carrier sensing in wireless communication systems

A wireless network device comprising a physical layer (PHY) module and a media access control (MAC) module. The PHY module is configured to communicate with an 80 MHz channel. The 80 MHz channel includes a plurality of sub-bands including a first sub-band, a second sub-band, a third sub-band, and a fourth sub-band. One of the plurality of sub-bands corresponds to a primary channel. The PHY module is further configured to determine which of the plurality of sub-bands are receiving a data packet, and generate at least one clear channel assessment signal indicating which of the plurality of sub-bands are receiving the data packet. The MAC module is configured to receive the at least one clear channel assessment signal from the PHY module, and selectively transmit on the primary channel based on the at least one clear channel assessment signal.

Coexistence mechanism for 802.11AC compliant 80 MHz WLAN receivers

Systems and methods for detecting data in a received multiple-input-multiple-output signal are provided. First, second, and third signals are received and form a vector y. The received signals are associated with first, second, and third data values that form a vector x. A channel matrix (H) is received, and a QR decomposition of the channel matrix is performed, such that H=QR. The vector y is transformed into a vector z according to z=Qy. A distance value between the rector z and the vector x is determined for each possible third data value. A nearest constellation point is calculated based on a first of the possible third data values. The calculating step is repeated for each of the possible third data values to generate a set of constellation point triplets. The distance values are determined using the set of constellation point triplets.

Low complexity technique for detecting data in a received multiple-input-multiple-output (MIMO) signal

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Cupertino, CA, United States of America

Ping Gao