To expand on this further.
The number of MFLOPS required is proportional to the sample-rate X inherent-flowgraph-complexity. If, on average, there's a deficit in available MFLOPS vs required MFLOPs, you'll get overflows. Buffering within the flow-graph, and the driver stacks, allows you to have short-term shortfalls, but if on average you don't have enough MFLOPs, you'll fall behind, and get overruns. Think of it as a kind of "physics of computing" thing. The more "stuff" you do in a flowgraph, the higher the inherent-flowgraph-complexity. A digital receiver DSP chain is quite complex, and requires a *lot* of operations to be performed on every sample. The architecture of Gnu Radio exacerbates this somewhat, because the data-flow model tends to produce redundant data motion that would not occur in a signal-processing chain that was "hand coded" and "hand optimized". It's the price you pay for the flexibility of the "plug a bunch of modules together" architecture. That being said, I have flow-graphs that run at 16.67Msps, doing "stuff" and they keep up fairly well--but on a 6-core 3.2GHz machine with 4G of fast memory. On 25 Mar 2013 10:36, Tom Rondeau wrote: > John, > > The ability to process data in a software radio application is > directly proportional to the sampling rate used. The higher the > sampling rate, the more computational power required. As you increase > the computational load on your application, each block takes longer to > process data, and at some point, your application can take too much > time, which means that the data flowing from the USRP to the host is > coming too fast to be processed, so it gets dropped. > > A digital receiver is a complex set of algorithms used to properly > synchronize (in time, frequency, and phase not to mention any > multipath distortions) the incoming signal. This is much more complex > than just drawing the signal in a GUI. > > So in other words, you shouldn't expect to be able to handle those > kinds of bandwidth with the digital receiver. Now, there's a lot more > optimization that can be done to make those algorithms more > computationally efficient in order to continue increasing the > potential symbol rate. > > Tom
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