Multiple Access, Resource Allocation and Capacity

Introduction and Context

A satellite transponder is a shared, expensive and power-limited communication resource. Multiple users, gateways, beams and services must therefore coexist while meeting requirements for throughput, delay, availability, spectral efficiency and quality of service (QoS). The multiple-access method determines how users share time, frequency, code, space or combinations of these dimensions. Resource allocation determines how bandwidth, power, coding rate, beams and transmission opportunities are assigned. Capacity analysis determines how much traffic the system can support under practical constraints.

These issues are especially important in high-throughput satellites (HTS), very-high-throughput satellites (VHTS), mobile satellite systems and broadband constellations. Modern systems increasingly combine frequency reuse, spot beams, adaptive coding and modulation, beam hopping, demand assignment and software-defined payloads. The design problem is consequently not simply to maximize raw bit rate; it is to optimize capacity while controlling interference, nonlinear distortion, latency, fairness, energy consumption and regulatory compliance.

Learning Objectives

By the end of this chapter, the reader should be able to:

1. Explain and compare FDMA, TDMA, CDMA, OFDMA, random access and demand-assigned multiple-access methods.

2. Analyze the effects of transponder nonlinearity, back-off and intermodulation.

3. Calculate basic link capacity and interpret bandwidth, power and interference constraints.

4. Explain frequency reuse, spot beams, beam hopping and scheduling strategies.

5. Formulate resource-allocation objectives and constraints for satellite networks.

6. Evaluate practical design trade-offs, including efficiency, fairness, latency, reliability and regulatory limitations.

1. Multiple Access as a Resource-Sharing Problem

Multiple access is the coordinated sharing of a communication medium by independent terminals. The principal resource dimensions are:

• Frequency: distinct carriers or subcarriers are assigned to users.
• Time: users transmit in separate time intervals.
• Code: users occupy overlapping time and frequency resources but use distinguishable spreading codes.
• Space: users are separated through spot beams, polarization, antenna patterns or spatial processing.
• Power and coding: transmission power and coding rates are adapted to channel conditions.

A satellite access scheme may be orthogonal, in which users are ideally separated in the allocated resource, or non-orthogonal, in which users overlap and are separated through interference cancellation, coding or statistical protocols. Orthogonality generally simplifies receiver design and interference management, whereas non-orthogonality may improve utilization when traffic is bursty or when advanced receivers are available.

The central design metrics include spectral efficiency, normally measured in bit/s/Hz; energy efficiency, measured in bit/J; delay; outage probability; packet loss probability; fairness; implementation complexity; and scalability. No single access method is best for every service.

2. Dedicated and Contention-Based Access Methods

2.1 Frequency Division Multiple Access

In FDMA, each user or carrier is assigned a frequency channel for a specified duration. Guard bands are inserted to limit adjacent-channel interference. A traditional satellite FDMA transponder may carry many simultaneous carriers, each with a fixed or semi-fixed bandwidth.

If the occupied bandwidth of carrier i is B_i and the required guard bandwidth between adjacent carriers is G_i, the approximate total allocated bandwidth is

B_total = Σ B_i + Σ G_i.

FDMA offers continuous transmission, low access delay and relatively simple terminal timing. It is suitable for constant-bit-rate voice, SCPC links and some VSAT networks. Its disadvantages are guard-band overhead, inefficient use of capacity under intermittent traffic, and sensitivity to transponder nonlinearities when many carriers share a high-power amplifier. Intermodulation products can fall into other carriers' channels.

FDMA systems often operate with input back-off (IBO) and output back-off (OBO). Back-off reduces amplifier drive or output power below saturation, decreasing nonlinear distortion at the cost of reduced power efficiency.

2.2 Time Division Multiple Access

TDMA assigns users non-overlapping time slots on a common carrier. A frame contains payload bursts, preambles, guard times and possibly control fields. If a frame has duration T_f and user i receives a payload interval T_i, the ideal duty fraction is T_i/T_f. In practice, the useful efficiency is lower because of guard times and overhead.

TDMA is effective for bursty or variable-rate traffic and permits centralized scheduling. It requires accurate timing, synchronization and ranging. In a satellite return link, propagation delay and terminal clock errors make guard intervals essential. A high peak-to-average power ratio may also occur when many terminals transmit short bursts.

2.3 Code Division Multiple Access

CDMA allows simultaneous transmission over the same frequency band using spreading codes. A signal is spread by a factor called the processing gain, approximately

G_p = R_c/R_b,

where R_c is the chip rate and R_b is the information bit rate, under the simplified assumption of binary spreading and comparable definitions of rates. At the receiver, correlation with the intended code despreads the desired signal while spreading much of the interference.

In an interference-limited CDMA system, capacity is soft rather than fixed: adding users gradually increases interference and decreases quality. Approximate capacity expressions depend on processing gain, target energy-per-bit to interference-plus-noise density ratio, voice activity, power control and other-user interference. Therefore, no single universal CDMA capacity formula applies without specifying the system model.

CDMA provides frequency diversity, resistance to narrowband interference and flexible asynchronous access. Its major challenges are near-far effects, stringent power control, code correlation, self-interference and relatively high receiver complexity.

2.4 Orthogonal Frequency Division Multiple Access

OFDMA divides a broadband channel into orthogonal subcarriers and assigns groups of subcarriers to users. Orthogonality is maintained when subcarrier spacing and timing satisfy the OFDM design conditions. A cyclic prefix absorbs multipath delay spread, but it consumes overhead.

OFDMA supports fine-grained allocation in both time and frequency. A scheduler can assign subcarriers with favorable channel conditions, improving throughput through multiuser diversity. Adaptive modulation and coding can be applied per resource block. However, OFDMA has high peak-to-average power ratio, which is particularly problematic for satellite terminals and payload amplifiers. Frequency offset, phase noise and nonlinear amplification can destroy subcarrier orthogonality.

Satellite OFDMA systems therefore require careful waveform design, crest-factor reduction, amplifier linearization or operation with adequate back-off. Variants such as single-carrier frequency division multiple access may be preferred in power-limited uplinks.

3. Random Access and Demand Assignment

3.1 Random Access

Random access allows a terminal to transmit without receiving an individual dedicated assignment for every packet. It is attractive for short, sporadic messages and large populations of low-duty-cycle terminals.

In pure ALOHA, a packet may be transmitted at any time. If the normalized offered load is G packets per packet duration, the ideal throughput is

S = G exp(-2G),

under the assumptions of equal packet duration, independent transmission attempts, no capture, and destructive collision of overlapping packets. The maximum occurs at G = 0.5 and is S_max = 1/(2e), approximately 0.184 packets per packet duration.

Slotted ALOHA restricts transmissions to slot boundaries. Its ideal throughput is

S = G exp(-G),

with maximum S_max = 1/e, approximately 0.368, when G = 1. These results are theoretical and do not include propagation delay, retransmission limits, coding, capture, synchronization overhead or channel errors.

Modern schemes such as contention resolution diversity slotted ALOHA transmit replicas of packets in multiple slots and use successive interference cancellation. They can substantially exceed classical ALOHA performance under suitable load and receiver assumptions, but require additional resources and sophisticated receiver processing.

3.2 Demand-Assigned Multiple Access

Demand-assigned multiple access (DAMA) allocates capacity in response to requests. A terminal may request a time slot, carrier, code, bandwidth or power level; a controller then grants resources according to policy and current availability. DAMA is well suited to variable traffic, although the request-grant process introduces delay and signaling overhead.

DAMA architectures may be centralized, distributed or hybrid. Centralized control provides global information and coordinated interference management but creates a control dependency and potential bottleneck. Distributed schemes can scale and react locally but may produce less globally efficient allocations.

A practical DAMA cycle includes request generation, request collection, admission control, scheduling, assignment dissemination, transmission and release or reassignment. Important policies include first-come-first-served, weighted fair queuing, minimum-rate guarantees, priority classes and optimization-based scheduling.

4. Transponder Nonlinearity and Multicarrier Operation

A satellite high-power amplifier (HPA), commonly a traveling-wave tube amplifier or solid-state power amplifier, is nonlinear near saturation. If x(t) is the input signal and y(t) is the output, a memoryless amplifier can be represented conceptually as

y(t) = A(|x(t)|) exp[j(arg x(t) + Φ(|x(t)|))],

where A represents amplitude conversion and Φ represents amplitude-dependent phase shift. This is an AM/AM and AM/PM model; actual devices may also exhibit memory effects.

For a single constant-envelope carrier, operation near saturation can be power efficient. For multicarrier FDMA or high-PAPR OFDM, however, nonlinear operation generates spectral regrowth and intermodulation products. These products cause adjacent-channel interference and distort the desired signal.

Two important measures are:

• Input back-off: the reduction in input power relative to the input level at saturation.
• Output back-off: the reduction in output power relative to saturated output power.

Back-off improves linearity but reduces effective isotropic radiated power and therefore link margin or capacity. In a shared transponder, the optimum operating point is a system-level compromise among carrier loading, adjacent-channel protection, power efficiency and service quality.

Intermodulation is especially serious when carriers have unequal powers. Power control, carrier grouping, predistortion, filtering, improved HPA operating points and single-carrier waveforms can reduce its effect. Engineers must distinguish thermal-noise limitation from interference limitation: increasing transmit power improves performance in the former but may worsen the latter when nonlinear or co-channel interference dominates.

5. Capacity Fundamentals

For an additive white Gaussian noise channel, the Shannon capacity is

C = B log₂(1 + S/N),

where C is capacity in bit/s, B is bandwidth in Hz, and S/N is the received signal-to-noise power ratio over the same bandwidth. This is an upper bound under ideal coding, arbitrarily long codewords and Gaussian noise. Practical systems replace the bound with a modulation and coding scheme that meets a specified block-error rate.

For a link with received carrier power C_r, noise power N and interference power I, the relevant ratio is often

C_r/(N + I).

If thermal noise is expressed by noise spectral density N₀ and the information rate is R_b, a useful design quantity is E_b/N₀. The relationship is

E_b/N₀ = (C_r/N₀)/R_b,

where C_r/N₀ has units of Hz and R_b is bit/s. With interference, an analogous expression uses interference-plus-noise density, provided the quantities are defined consistently.

Satellite capacity is constrained by several resources simultaneously:

1. Bandwidth constraint: finite transponder spectrum and regulatory allocations.

2. Power constraint: finite payload amplifier power and terminal transmit power.

3. Interference constraint: adjacent beams, adjacent satellites, polarization leakage and intermodulation.

4. Gateway and feeder-link constraint: limited gateway antennas, spectrum and processing.

5. Terminal constraint: antenna size, battery energy, oscillator quality and hardware cost.

6. Traffic constraint: spatially and temporally varying demand.

Consequently, a link may be bandwidth-limited, power-limited, interference-limited or gateway-limited. A nominal transponder bandwidth alone is not a reliable measure of network capacity.

Worked Example: Bandwidth-Limited Throughput

A downlink has 36 MHz of usable bandwidth. A practical waveform achieves 2.5 bit/s/Hz after modulation, coding and protocol overhead. The net throughput is

R = 36 × 10⁶ × 2.5 = 90 × 10⁶ bit/s,

or 90 Mbit/s. This result assumes that the stated spectral efficiency already includes implementation and overhead losses. If 20% of the physical rate is reserved for framing and control, the user throughput is

R_user = 0.8 × 90 = 72 Mbit/s.

The calculation does not establish whether 72 Mbit/s is deliverable at all times: power margin, rain attenuation, interference and scheduling may reduce actual service.

6. Frequency Reuse and Spatial Capacity

Frequency reuse allows nonadjacent or sufficiently isolated beams to use the same spectrum. A multibeam satellite can therefore provide much greater aggregate capacity than a single wide beam using the same nominal frequency allocation.

Reuse is enabled by narrow spot beams, polarization discrimination and antenna pattern design. Its cost is co-channel interference. If beam k receives desired power S_k and interference from other beams I_k, its quality is governed by S_k/(N_k + I_k). Increasing the number of reuse clusters may increase total offered spectrum per geographic area but reduce carrier-to-interference ratio.

Four-color reuse traditionally separates frequency and polarization among neighboring beams. Aggressive reuse may use the same frequencies in every beam with advanced beam shaping, precoding or interference coordination. The appropriate reuse pattern depends on antenna sidelobes, user distribution, gateway geometry, polarization isolation and required service availability.

Spatial frequency reuse changes capacity planning from a single transponder problem to a network optimization problem. Beam footprints must be designed with coverage, handover, rain zones, gateway visibility and regulatory power-flux-density limits in mind.

7. Beam Hopping and Scheduling

Beam hopping dynamically illuminates selected spot beams rather than continuously serving every beam. A payload switch matrix or digital processor assigns time-varying power and bandwidth to beams according to traffic demand.

A beam-hopping frame may contain a sequence of illumination patterns. The scheduler must account for:

• queue backlogs and predicted demand;
• minimum service guarantees;
• beam switching time and payload constraints;
• feeder-link availability;
• user mobility and handover;
• rain attenuation and link margin;
• interference among simultaneously active beams;
• fairness and latency requirements.

Beam hopping is powerful when traffic is geographically uneven or changes over time. It can concentrate power where it has the greatest marginal value. Its limitations include switching overhead, synchronization complexity, transient interference, service interruptions and the possibility that a demand prediction error produces poor allocations.

A useful scheduling objective can be written abstractly as

maximize Σ_t Σ_b U_b(R_b,t) − λP_t − μD_t,

subject to bandwidth, power, beam-activation, interference and minimum-service constraints. Here R_b,t is the rate allocated to beam b at time t; U_b is a utility function; P_t represents resource or power use; D_t represents delay or unmet demand; and λ and μ are policy weights. This is a framework rather than a universal formula. The exact optimization depends on whether the objective is revenue, throughput, fairness, energy efficiency or service-level compliance.

Concave utility functions often promote fairness, whereas a pure sum-rate objective favors users with favorable channels. Weighted utilities can prioritize emergency communications, public safety or premium services. A scheduler must not silently sacrifice contracted minimum rates for aggregate throughput.

8. Resource Allocation Models

Resource allocation may be static, semi-static or dynamic.

• Static allocation: resources are assigned for long periods. It is simple and predictable but inefficient for variable demand.
• Semi-static allocation: recurring plans are updated periodically using traffic forecasts.
• Dynamic allocation: resources are reassigned in near real time using queue and channel information.

Typical decision variables include carrier bandwidth, time-slot duration, subcarrier assignment, transmit power, coding and modulation, beam activation and gateway selection. Common constraints include

Σ_i b_i ≤ B,

Σ_i p_i ≤ P,

R_i ≥ R_i,min,

and interference I_j ≤ I_j,max,

where b_i and p_i are bandwidth and power assigned to user or beam i, B and P are available totals, R_i,min is a minimum service rate, and I_j,max is an interference limit at receiver j.

The constraints may be coupled. For example, increasing modulation order can increase rate but require higher signal-to-interference-plus-noise ratio; increasing power may improve one beam while increasing interference in another; and selecting a narrow beam may increase spatial reuse while reducing coverage area.

Exact mixed-integer optimization can be computationally difficult because assignment and activation variables are discrete while power and rate variables are continuous. Practical systems therefore use heuristics, decomposition, convex approximations, queue-aware scheduling, reinforcement learning or combinations of these.

Role of Artificial Intelligence

Machine learning is relevant when traffic, channel conditions and rain attenuation are difficult to model precisely. Forecasting models can predict beam demand, while reinforcement learning can learn scheduling policies. However, AI should not replace link-budget validation or safety constraints. Training data may be biased toward normal weather and ordinary traffic, causing poor behavior during disasters or rare interference events. Operational systems require explainable constraints, safe fallback policies, cybersecurity protection and monitoring of model drift.

9. Applied Case: Illustrative HTS Capacity Planning Scenario

Background

Consider an illustrative Ka-band HTS with 24 spot beams. Each beam can support up to 100 Mbit/s during an illuminated time interval. The payload has sufficient aggregate power to illuminate eight beams simultaneously. Demand is highly uneven: four urban beams require approximately 80 Mbit/s each, eight suburban beams require 35 Mbit/s each, and twelve rural beams require 10 Mbit/s each during the busy hour.

Problem

Continuous illumination would waste power in rural beams while failing to provide enough capacity in urban beams. A static equal allocation would also be inefficient. The operator must meet minimum rural service, support urban demand and avoid excessive co-channel interference.

Analysis

The instantaneous demand is

4(80) + 8(35) + 12(10) = 920 Mbit/s.

The maximum simultaneous payload capacity is

8(100) = 800 Mbit/s.

Therefore, all demand cannot be served simultaneously at peak values. Scheduling across time is necessary. If the busy-hour demand is averaged over a sufficiently long period and beam queues are stable, the system can serve more than 800 Mbit/s of instantaneous demand by time sharing, but only if the average offered load and latency requirements permit it.

Approach

A beam-hopping policy reserves minimum service for all rural beams, gives additional illumination to urban beams, and uses queue length and predicted demand to adjust the pattern. Suppose a 10-slot scheduling frame is used. Rural beams receive at least one slot each where feasible; urban beams receive multiple slots, while suburban beams receive intermediate allocation. Adjacent beams using the same frequencies are not illuminated together when their interference would violate the carrier-to-interference target. Adaptive coding reduces the rate during rain events rather than allowing repeated packet loss.

The scheduler uses weighted utility: emergency and contracted traffic receives high priority, while elastic broadband traffic is scheduled according to queue length and channel quality. The gateway controller also reserves feeder-link capacity, since downlink beam capacity is useless if gateway processing or feeder spectrum is unavailable.

Outcome

The approach improves utilization compared with continuous equal illumination, but it cannot create capacity beyond the average power, bandwidth and feeder-link limits. During simultaneous rain events over several urban beams, the system must reduce modulation and coding, defer elastic traffic or invoke an overflow gateway. The result illustrates that capacity optimization is a cross-layer problem involving payload, gateway, terminal and service policy.

Learning Points

1. Peak aggregate demand can exceed instantaneous payload capacity even when average demand is supportable.

2. Beam hopping converts spatial demand variation into a scheduling opportunity.

3. Frequency reuse increases capacity only when interference remains acceptable.

4. Minimum-service and fairness constraints are as important as sum throughput.

5. Adaptive coding and realistic weather assumptions are essential for availability planning.

10. Comparison of Access Methods

FDMA is simple and continuous but consumes guard bands and requires nonlinear multicarrier management. TDMA is flexible and efficient for burst traffic but requires accurate synchronization. CDMA supports asynchronous operation and frequency diversity but is interference- and power-control-limited. OFDMA offers fine-grained scheduling and multiuser diversity but has high peak-to-average power ratio and demanding synchronization requirements. Random access is efficient for short sporadic traffic at light load but suffers collisions at high load. DAMA improves utilization for variable traffic but adds signaling delay and control complexity.

The selection should be based on traffic statistics, terminal power, propagation delay, payload linearity, required latency, mobility, regulatory constraints and the maturity of the control architecture. Hybrid systems are common: for example, contention-based access may request resources, DAMA may assign a TDMA burst, and adaptive coding may select the physical-layer mode.

11. Challenges, Governance and Best Practices

Important challenges include long propagation delay, rain fading, oscillator instability, beam-edge interference, imperfect traffic forecasts, HPA distortion, gateway failures and cyberattacks against control channels. Satellite operators must coordinate orbital and spectrum use under applicable national regulations and International Telecommunication Union procedures. Equivalent isotropically radiated power, out-of-band emissions, power-flux-density limits and inter-satellite or terrestrial interference must be controlled.

Best practices include:

• separate link-budget, interference-budget and capacity-budget analyses;
• model nonlinear payload behavior using measured or validated HPA characteristics;
• include guard times, coding overhead, pilot fields, retransmissions and control traffic;
• evaluate both average and percentile demand, including disaster and event scenarios;
• reserve capacity for control, emergency and restoration traffic;
• test schedulers under stale information and failed gateways;
• use admission control rather than promising infeasible peak rates;
• validate AI policies against deterministic safety and regulatory constraints;
• monitor actual carrier-to-interference ratio, spectral regrowth and queue delay after deployment.

Contemporary Developments

Digital transparent processors and regenerative payloads enable flexible channelization, routing and beam formation. Multi-beam satellites increasingly use aggressive frequency reuse, digital beamforming and precoding. Non-terrestrial network integration with 5G and later systems introduces standardized service management, mobility and interoperability requirements. Onboard processing can shorten control loops and reduce dependence on a central gateway, but it increases payload complexity and radiation-hardening requirements.

Research continues on non-orthogonal multiple access, integrated terrestrial-satellite scheduling, cell-free or coordinated satellite beams, optical feeder links, energy-aware operation, quantum-safe control security and learning-assisted resource allocation. These developments do not eliminate fundamental limits: spectrum, power, interference, propagation conditions and finite processing resources remain binding constraints.

Chapter Summary

Multiple access determines how satellite users share frequency, time, code and spatial resources. FDMA provides continuous dedicated carriers but suffers guard-band and nonlinear multicarrier penalties. TDMA supports burst traffic through scheduled time slots, while CDMA trades bandwidth and power control against soft interference-limited capacity. OFDMA enables detailed time-frequency scheduling but is sensitive to peak-to-average power and synchronization. Random access is appropriate for low-duty-cycle traffic, whereas DAMA allocates resources according to demand and QoS policy.

Satellite capacity is governed by bandwidth, received power, interference, amplifier linearity, gateway resources and traffic variability. Shannon capacity provides an ideal upper bound, but practical throughput depends on coding, overhead, rain attenuation, nonlinear distortion and availability targets. Frequency reuse and spot beams increase aggregate capacity, while beam hopping exploits changing spatial demand. Scheduling must balance throughput, fairness, latency, power, interference and contractual guarantees. Effective engineering therefore requires cross-layer optimization rather than isolated selection of a waveform or transponder.

Key Terms

Multiple access: Sharing a communication medium among independent users.

FDMA: Access method assigning separate frequency channels to users.

TDMA: Access method assigning separate time intervals to users.

CDMA: Access method distinguishing users by spreading codes.

OFDMA: Multiuser OFDM method assigning subcarriers or resource blocks to users.

Random access: Access in which terminals contend for transmission opportunities.

DAMA: Demand-assigned multiple access controlled by resource requests and grants.

Guard band: Unused frequency separation that limits adjacent-channel interference.

Processing gain: Ratio of spread-spectrum chip rate to information rate.

Transponder: Satellite subsystem that receives, processes or translates and retransmits signals.

High-power amplifier: Payload amplifier that provides transmit power and may introduce nonlinear distortion.

Input back-off: Reduction of amplifier input drive below saturation reference.

Intermodulation: Nonlinear generation of frequency components from multiple carriers.

Frequency reuse: Reuse of spectrum in spatially separated or sufficiently isolated beams.

Beam hopping: Dynamic illumination of selected beams according to demand.

Spectral efficiency: Throughput per unit bandwidth, usually bit/s/Hz.

Carrier-to-interference-plus-noise ratio: Ratio of desired carrier power to interference plus noise.

Fairness: Degree to which resource allocation meets equitable service objectives.

Admission control: Decision process determining whether new traffic can be supported.

Review Questions

Short Answer Questions

1. What are the principal resource dimensions used in satellite multiple access?

2. Why does an FDMA transponder require input or output back-off?

3. State one major advantage and one limitation of TDMA.

4. What is the purpose of a guard interval in TDMA?

5. Distinguish random access from demand-assigned access.

Long Answer Questions

1. Compare FDMA, TDMA, CDMA and OFDMA in terms of efficiency, synchronization, power amplifier requirements and applications.

2. Explain how transponder nonlinearity produces intermodulation and how back-off mitigates it.

3. Discuss the relationship between frequency reuse, spot beams and co-channel interference.

4. Explain the role of beam hopping in a high-throughput satellite and identify its operational limitations.

5. Describe a resource-allocation framework that jointly considers power, bandwidth, interference and QoS.

Analytical / Application Questions

1. A 36 MHz transponder supports 2.5 bit/s/Hz, including physical-layer coding but excluding a 20% protocol overhead. Calculate the user throughput and state the assumptions.

2. Explain why a system can have adequate average capacity but still fail to serve peak urban demand. Propose two scheduling or architectural remedies.

3. Select an access strategy for a low-duty-cycle sensor network and a high-rate broadband gateway. Justify the choices using traffic, latency, synchronization and power considerations.

Multiple Choice Questions with Answers

Question 1

Which multiple-access method assigns users distinct frequency channels?

A. FDMA

B. TDMA

C. CDMA

D. Random access

Correct Answer: A. FDMA

Question 2

Under ideal pure ALOHA assumptions, the maximum normalized throughput is approximately:

A. 0.184

B. 0.368

C. 0.500

D. 1.000

Correct Answer: A. 0.184

Question 3

What is the principal purpose of amplifier back-off in a multicarrier satellite transponder?

A. To increase propagation delay

B. To reduce nonlinear distortion and intermodulation

C. To eliminate all thermal noise

D. To increase guard-band width automatically

Correct Answer: B. To reduce nonlinear distortion and intermodulation

Question 4

OFDMA primarily allocates which resources among users?

A. Satellite orbits only

B. Subcarriers or time-frequency resource blocks

C. Spreading codes only

D. Antenna reflector panels only

Correct Answer: B. Subcarriers or time-frequency resource blocks

Question 5

A 36 MHz channel with spectral efficiency of 2.5 bit/s/Hz has a physical-layer rate of:

A. 14.4 Mbit/s

B. 72 Mbit/s

C. 90 Mbit/s

D. 144 Mbit/s

Correct Answer: C. 90 Mbit/s

Question 6

Which method is most directly designed to serve sporadic short messages without a prior dedicated assignment?

A. Pure FDMA

B. Random access

C. Continuous SCPC

D. Fixed carrier TDMA only

Correct Answer: B. Random access

Question 7

Frequency reuse increases aggregate satellite capacity mainly by:

A. Using the same spectrum in spatially separated beams

B. Removing all propagation delay

C. Making every amplifier perfectly linear

D. Eliminating the need for gateways

Correct Answer: A. Using the same spectrum in spatially separated beams

Question 8

In the Shannon expression C = B log₂(1 + S/N), B denotes:

A. Coding gain

B. Occupied bandwidth in hertz

C. Packet error rate

D. Beam diameter

Correct Answer: B. Occupied bandwidth in hertz

Question 9

What is a major limitation of OFDMA in satellite terminals?

A. It cannot support variable rates

B. It has high peak-to-average power ratio

C. It requires no synchronization

D. It cannot use frequency reuse

Correct Answer: B. It has high peak-to-average power ratio

Question 10

Beam hopping is best described as:

A. Permanent illumination of every beam at equal power

B. Dynamic illumination of selected beams according to demand

C. Random deletion of all low-rate users

D. Changing the satellite orbit every frame

Correct Answer: B. Dynamic illumination of selected beams according to demand