Inputs
Example data table
| Scenario | Modulation | Rs (Mbaud) | α | Code rate | Streams | Channels | Overhead | Net bitrate (Mbps) | BW (MHz) |
|---|---|---|---|---|---|---|---|---|---|
| Link A | QPSK | 10 | 0.25 | 3/4 | 1 | 1 | 5% | 56.250 | 12.500 |
| Link B | 16QAM | 20 | 0.20 | 5/6 | 1 | 1 | 8% | 122.667 | 24.000 |
| Link C | 64QAM | 30 | 0.10 | 3/4 | 2 | 1 | 10% | 729.000 | 33.000 |
| Link D | 256QAM | 25 | 0.15 | 9/10 | 2 | 2 | 12% | 3168.000 | 28.750 |
Formula used
- bitsPerSymbol = log2(M)
- R_gross = Rs × bitsPerSymbol × streams × channels
- R_net = R_gross × codeRate × (1 − overhead)
- BW ≈ Rs × (1 + α) (raised-cosine / RRC approximation)
- η = R_net / BW (spectral efficiency, b/s/Hz)
How to use this calculator
- Select a calculation mode: bitrate, required symbol rate, or required bandwidth.
- Pick a modulation (or choose Custom and enter M).
- Set rolloff α and FEC code rate. Add overhead if you have framing/pilot estimates.
- Enter symbol rate, or enable bandwidth derivation and enter bandwidth.
- For “required” modes, enter the target net bitrate.
- Press Calculate to see gross, net, bandwidth, and spectral efficiency.
- Use the CSV/PDF buttons in Results for exporting.
Modulation bitrate planning overview
Digital links trade speed, robustness, and occupied bandwidth. This calculator connects symbol rate, modulation order, coding, and overhead into a clear net throughput estimate. Use it for radios, satellite carriers, microwave backhaul, SDR experiments, and lab validation when you need quick, consistent numbers.
1) Symbol rate and payload speed
Symbol rate (Rs) is the pace of constellation updates in symbols per second. For a fixed Rs, higher-order constellations carry more bits per symbol using log2(M). Example: QPSK carries 2 bits/symbol, 16QAM carries 4, and 64QAM carries 6.
2) Modulation order and SNR demand
Increasing M improves raw throughput but requires cleaner channels. Practical systems move between QPSK, 16QAM, 64QAM, and 256QAM as SNR changes. Adaptive modulation often targets a packet error rate while maximizing spectral efficiency.
3) FEC code rate impact
Forward error correction adds redundancy. Code rate is the fraction of useful bits after coding. A 1/2 rate roughly halves net throughput, while 3/4 retains 75%. Stronger codes increase reliability at the expense of speed.
4) Overhead and real throughput
Protocols consume capacity for pilots, headers, guards, and framing. Overhead is modeled as a percentage reduction. For instance, 10% overhead means only 90% of coded bits become payload. This helps align estimates with measured application throughput.
5) Rolloff and occupied bandwidth
Pulse shaping changes the required spectrum. With raised-cosine or RRC shaping, occupied bandwidth is approximated by BW ≈ Rs(1+α). A smaller rolloff α improves bandwidth efficiency, but filters become sharper and timing becomes more sensitive.
6) Streams and channel aggregation
Multiple spatial streams (MIMO layers) multiply throughput when channels are sufficiently independent. Channel aggregation represents bonded carriers or parallel channels. This calculator multiplies gross rate by both factors to reflect layered or bonded systems.
7) Spectral efficiency as a KPI
Net spectral efficiency, in b/s/Hz, summarizes performance. Higher values mean more payload per unit spectrum. Compare configurations with the same bandwidth to see whether higher M and lighter coding genuinely improve efficiency after overhead.
8) Quick sanity checks
Start with known Rs and α, then review estimated bandwidth. Next confirm that gross and net bitrates match expectations for your modulation and coding. If your measured throughput is lower, increase overhead to represent pilots, MAC scheduling, retransmissions, or framing losses.
FAQs
1) What is the difference between gross and net bitrate?
Gross bitrate counts raw bits from modulation at the symbol rate. Net bitrate applies FEC code rate and overhead, estimating payload bits delivered after coding and protocol reductions.
2) Which bandwidth formula does the calculator use?
It uses the common raised-cosine approximation: bandwidth is symbol rate times (1 + rolloff). Real occupied bandwidth depends on filter design, masks, and implementation details.
3) How do I choose rolloff α?
Typical values are 0.35, 0.25, or 0.20. Lower α improves bandwidth efficiency but needs sharper filtering and can increase sensitivity to timing and imperfections.
4) Why does stronger FEC reduce throughput?
Stronger coding adds more redundancy to correct errors, so fewer transmitted bits are payload. The calculator models this using the code rate multiplier.
5) What overhead value should I enter?
Use a measured or estimated percentage for pilots, guards, framing, headers, and similar costs. If uncertain, start with 5–15% and adjust until net bitrate matches real throughput.
6) Can I model MIMO or carrier bonding?
Yes. Increase spatial streams for independent layers, and increase channel aggregation for bonded carriers. Throughput scales linearly in the calculator.
7) Does higher modulation always mean higher performance?
Not always. Higher orders need higher SNR and may force retransmissions or stronger coding. Net throughput can drop if link quality cannot support the chosen constellation.