RF Stuff

It has often bewildered a great many RF Engineers when it comes to answering this question, “How do you measure the cell throughput during the busy hour?”. There are two camps, the first (1) would go about by getting the sum of all data transferred per QCI (in Mb) and divide it with the sum of the time for each data transfer per QCI (seconds) duration, the other (2) would get the individual transfer rates per QCI and the sum of all transfer rates would be the cell’s data transfer rate at any given hour - which I think is the correct one considering the ridiculous results you get when using the first method.

It’s most interesting when you put RQI’s (Radio Quality Indicators) side by side and see how they influence your throughput. The following table serves to illustrate the range of throughput fluctuations per bandwidth at varying radio conditions: At extremely low CQI ranges, equivalent to poor radio interface quality, the fluctuations are rather large (10%-30%) representing a very bad perceived experience in terms of throughput. It is therefore suggested that for CQI targets should be set around CQI=10 to guarantee excellent subscriber experience.

Everyone gets excited everytime a feature comes out especially those that claims to improve the subscriber experience in terms of throughput by a factor of 50%-100%. Question is: Under the same radio conditions can 256QAM deliver on its promise? First, it’s definitely handset capability dependent. The phones that support such capability would be, at the minimum, the Galaxy S8 - and all the succeeding high-end batches. Practically we’re looking at less than 1% of all the LTE capable mobile handsets out there - well, at least as of this writing.

Coverage has great impact on LTE subscriber experience when one considers Gap Measurement occurrences in a highly mobile environment where handover happens due to coverage limitation. It can be said that the number of gap measurement occurences is a measure of the coverage continuity of a cluster - if extended, coverage continuity of an LTE network. Coverage assessment could be effectively done using the RATA (Random Access per Timing Advance) indices.

The operations engineer’s perspective is critical for the assessment of the current usage of the networks bandwidth resources as it reflects whether the planning assumptions were close to actual performance or not - not to start a fight between the operations and planning department. Spectrum efficiency, although is much understood to be a planning parameter, should also be part of the monitoring of operations engineers. However, for most, if it’s not clearly understood it is altogether ignored.

LTE IPPM Strategic Deployment Telcos are in a race to secure confidence among their subscribers and its not surprising that technical people are put to work to secure the end-to-end subscriber experience measured primarily in terms of speed - or more technically, the throughput. One peculiar matter for the LTE is its sensitivity to delay - were talking about a base requirement of 10ms which correspondes to the LTE Radio frame.

Description of The Algorithm Determine cluster average site to site distance. Get the distance to 5 closest neighbor, the average of which is to be considered the average effective linear coverage - half of which is the -3dB point. I found an article in stackoverflow giving illustration to solve this problem using the fossil package. The -3dB coverage point. Recall that antenna propagation is typically illustrated by the following figure: Note that the -3dB point defines the farthest extent of a sector antenna’s coverage.

According to basic information theory, Capacity is proportional to bandwidth, the antenna deployment strategy/technology and radio access interface quality - expressed in terms of SINR. Some Radio engineering departments have the KPIs mostly to evaluate equipment performance, others adopted KQIs to include the end-to-end experience. The adoption of RQIs - Radio Quality Index is essential to provide quality metrics to operations teams as it translates closer to user experience. This shall consist mainly of SINR, CQI, Spectrum efficiency, MCS, Radio BLER counters, EVQI and Throughput.

The following proposed LTE IPPM KPI Monitoring thresholds are set for both S1 and X2 transport links. Interface BackJitter ForwardJitter Rtt PLR S1 <4ms <4ms <20ms <0.001% X2 <4ms <4ms <8ms <0.001% S1 IPPM monitoring implementation varies among network operators, at least, for my experience depends on the UGW strategy. If the UGW are “pooled” then it is imperative to define ip session to every UGW there is in the network, which in itself is a daunting task, depending on where you are, you are looking at 100+ ip session per node.