Edge Weight Power and Frequency Assignment Algorithm

In cellular networks, cells are grouped more densely around highly populated areas to provide more capacity.  Antennas are pointed in accordance with local terrain and clutter to reduce signal shadows and interference. Hardware parameters are easily set during installation but difficult to change thereafter. In a dynamic environment of population migration, there is need to continuously tune network parameters to adapt the network performance. Modern mobile equipment logs network usage patterns and statistics over time. This information can be used to tune soft parameters of the network. These parameters may include frequency channel assignment or reuse, and transmitter radiation power assignment to provide more capacity on demand. The paper proposes that by combining the frequency and power assignments, further optimisation in resource allocation can be achieved over a traditional frequency assignment. The solution considers the interference, traffic intensity and use of priority flags to bias some edges. An Edge Weight Power and Frequency Assignment Algorithm is presented to solve the resource allocation problem in cellular networks. The paper also analyses the performance improvements obtained over that of the Edge Weight Frequency Assignment Algorithm. The results show that the proposed algorithm improves the performance of the Edge Weight Frequency Assignment Algorithm depending on the initial structure of the graph

Edge Weight Power and Frequency Assignment Algorithm

In cellular networks, cells are grouped more densely around highly populated areas to provide more capacity.  Antennas are pointed in accordance with local terrain and clutter to reduce signal shadows and interference. Hardware parameters are easily set during installation but difficult to change thereafter. In a dynamic environment of population migration, there is need to continuously tune network parameters to adapt the network performance. Modern mobile equipment logs network usage patterns and statistics over time. This information can be used to tune soft parameters of the network. These parameters may include frequency channel assignment or reuse, and transmitter radiation power assignment to provide more capacity on demand. The paper proposes that by combining the frequency and power assignments, further optimisation in resource allocation can be achieved over a traditional frequency assignment. The solution considers the interference, traffic intensity and use of priority flags to bias some edges. An Edge Weight Power and Frequency Assignment Algorithm is presented to solve the resource allocation problem in cellular networks. The paper also analyses the performance improvements obtained over that of the Edge Weight Frequency Assignment Algorithm. The results show that the proposed algorithm improves the performance of the Edge Weight Frequency Assignment Algorithm depending on the initial structure of the graph

Analysis of sensor impulse response effects on Cramèr–Rao lower bounds for signal parameter estimators

In this study, a generic analysis of sensor impulse response effects on linearly filtered channel noise is presented to illustrate the resulting variations to the Cramèr–Rao lower bounds (CRLBs) of signal parameter estimators in signal processing and communication applications. The authors start by deriving the density function of a filtered signal, which is shown to be a mixture density, and hence the exact expressions for the mean and variance. Simulation results are used to confirm the derivations, which are then used to investigate the effects of impulse response length and variance, as well as channel noise length and variance effects on the resulting CRLBs. Results indicate that for non-zero-mean channel noise and impulse responses, the resulting mean of filtered noise can be relatively large causing adverse deviations to parameter estimations. The filtered noise variance is shown to be proportional to the impulse response energy, where for long duration of signal capture the CRLB is significantly increased