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Frequency-hopping spread spectrum (FHSS) is a method of transmitting radio signals by rapidly changing the carrier frequency among many frequencies occupying a large spectral band. The changes are controlled by a code known to both transmitter and receiver .
Soon after, machine learning based techniques that generate sequences of a desired length and spreading properties have been published as well. These are highly competitive with the classic Gold and Welch sequences. These are not generated by linear-feedback-shift-registers, but have to be stored in lookup tables.
The OFDM diversity gain and resistance to frequency-selective fading may partly be lost if very few sub-carriers are assigned to each user, and if the same carrier is used in every OFDM symbol. Adaptive sub-carrier assignment based on fast feedback information about the channel, or sub-carrier frequency hopping, is therefore desirable.
Most 2G cellular systems, with the notable exception of IS-95, are based on TDMA. GSM, D-AMPS, PDC, iDEN, and PHS are examples of TDMA cellular systems.. In the GSM system, the synchronization of the mobile phones is achieved by sending timing advance commands from the base station which instruct the mobile phone to transmit earlier and by how much.
For mobile phone technology, a mobile allocation index offset (MAIO) refers a time delay separating traffic channels.When a GSM (Global System for Mobile Communications) mobile phone is served by a cell that is hopping over a set of frequencies, the separate traffic channels hop over the allocated frequencies according to a hopping sequence number (HSN).
Practical synchronous digital systems radiate electromagnetic energy on a number of narrow bands spread on the clock frequency and its harmonics, resulting in a frequency spectrum that, at certain frequencies, can exceed the regulatory limits for electromagnetic interference (e.g. those of the FCC in the United States, JEITA in Japan and the ...
One of the key challenges of the cognitive radio based wireless networks, such as IEEE 802.22 wireless regional area networks (WRAN), [1] is to address two apparently conflicting requirements: assuring Quality of Services (QoS) satisfaction for services provided by the cognitive radio networks, while providing reliable spectrum sensing for guaranteeing licensed user protection.
In learning a discretized function, the DNN first fits the continuous low-frequency components of the discretized function, i.e., large entropy state. Then, the DNN output tends to be discretized as the network gradually captures the high-frequency components, i.e., entropy decreasing. Thus, the compression phase appears in the information plane.