Satellite Communication Traffic Quiz

One Erlang represents the continuous use of one voice path. In satellite systems, it corresponds to one channel being occupied for the entire hour. If a channel is used for 30 minutes in an hour, it carries 0.5 Erlangs. This dimensionless unit is fundamental to traffic engineering as it allows comparison of traffic loads independent of time units.

Traffic intensity A = λ × h, where λ is arrival rate (calls/time) and h is average holding time. First, convert holding time to hours: 5 minutes = 5/60 = 0.0833 hours. Then A = 120 calls/hour × 0.0833 hours/call = 10 Erlangs. This means on average, 10 channels would be simultaneously occupied.

The Erlang B formula (also known as Erlang's loss formula) calculates blocking probability for systems with Poisson arrivals, exponential holding times, and no queuing (blocked calls are cleared). This is appropriate for most satellite voice circuits where a busy signal is returned if no channel is available. Erlang C is used for systems with queuing.

The busy hour is the 60-minute period with the highest traffic load. Satellite systems are designed to handle this peak load to ensure acceptable service quality during the most demanding periods. Designing for average traffic would result in unacceptable blocking during peak usage times. The busy hour varies by service type, time zone, and user patterns.

For a fixed offered traffic load, increasing the number of channels (servers) always decreases blocking probability in the Erlang B model. More channels mean a lower probability that all channels are busy when a call arrives. The relationship is non-linear—adding channels when the system is heavily loaded (high utilization) produces a more significant reduction in blocking than when it's lightly loaded.

The significant propagation delay in GEO satellite systems (approx. 240 ms one-way, 540 ms round-trip) has multiple traffic implications: (1) It increases effective holding time for conversational services due to longer pauses and slower interactions; (2) It reduces the number of Erlangs a channel can effectively carry because of protocol overheads and retransmissions; (3) It often requires more aggressive forward error correction, which reduces effective information capacity.

DAMA dynamically allocates satellite capacity based on actual demand, making it highly efficient for bursty data traffic. Unlike fixed allocation methods (FDMA, TDMA with fixed slots), DAMA assigns bandwidth only when users have data to send, reducing wasted capacity during idle periods. Modern satellite systems often combine DAMA with TDMA or MF-TDMA (Multi-Frequency TDMA) for optimal efficiency.

Traffic concentration takes advantage of the statistical nature of user demand. Since not all users need maximum capacity simultaneously, concentrated traffic allows fewer satellite channels to serve many users while maintaining acceptable blocking probability. This statistical multiplexing gain is expressed as Concentration Ratio = Number of users / Number of channels, typically ranging from 5:1 to 20:1 in satellite systems.

Grade of Service (GoS) is typically expressed as the probability that a call will be blocked due to insufficient resources. A GoS of 0.01 means a 1% blocking probability during the busy hour. This is a key design parameter balancing service quality against infrastructure cost. For critical services, GoS might be 0.001 (0.1% blocking) or better, while for non-critical services, 0.02-0.05 (2-5% blocking) may be acceptable.

Rain fade causes signal attenuation at higher frequencies (especially Ku and Ka bands). To maintain link reliability during rain events, systems must either: (1) Increase transmission power (reducing battery life on mobile terminals), (2) Reduce data rates (adaptive coding and modulation), or (3) Implement site diversity. All these approaches effectively reduce the traffic capacity that can be reliably supported, requiring traffic engineering to account for weather-induced capacity variations.

Offered traffic is the total traffic load presented to the system, including calls that will be blocked due to insufficient capacity. Carried traffic is the actual traffic successfully handled by the system. The difference (offered - carried) represents the traffic lost due to blocking. This relationship is fundamental: Carried Traffic = Offered Traffic × (1 - Blocking Probability).

DAMA systems monitor traffic intensity from each terminal and allocate satellite resources (bandwidth, timeslots) dynamically based on actual need. When traffic intensity from a terminal increases, it requests and receives more resources; when traffic decreases, resources are released for other users. This demand-based allocation provides much higher efficiency than fixed allocation schemes, especially for variable-rate services like internet access or intermittent voice calls.