Ieee Methods

IEEE Methods and Reproducibility

Use this skill to turn a method description into a reproducible IEEE communications methods block. It sits between ieee-writing and ieee-experiments: writing explains the idea; this skill makes the implementation, notation, and complexity auditable.

Core stance

• Reproducible beats impressive. A reviewer should be able to rebuild the main curve from the

system model, parameter table, algorithm box, and solver/training details.

• Define every symbol at first use. If a variable appears in an equation, it needs a domain,

dimension, unit when relevant, and role.

• Separate assumptions from simplifications. Assumptions define the studied regime;

simplifications need a boundary or robustness check.

• Complexity claims need variables. State big-O in terms of antennas/users/subcarriers/RIS

elements/iterations, not a vague "low complexity".

• No hidden implementation. Solver version, stopping tolerance, Monte-Carlo realization count,

train/test split, and randomization policy are methods content, not footnotes.

When to open extra files

| File | Open when | |---|---| | [references/reproducibility-checklist.md](references/reproducibility-checklist.md) | Auditing or writing system/channel setup, simulation-parameter tables, randomization, solvers, training data, hardware/testbed/ray-tracing settings, or reproducibility statements | | [references/notation-and-complexity.md](references/notation-and-complexity.md) | Building notation tables, algorithm boxes, convergence statements, or big-O complexity analysis |

Use ieee-writing for full Section II/III prose, ieee-experiments for benchmark/metric design, ieee-figure for result plots, and ieee-latex for IEEEtran formatting and compilation.

Workflow

1. Identify the method object: system model, problem formulation, algorithm, analysis, neural

network, simulation protocol, or testbed/ray-tracing setup.

1. Extract the reproducibility variables: topology, channel, signal model, optimization

variables, metrics, solver/training setup, and random quantities.

1. Build a notation table for nontrivial papers: symbol, size/domain, meaning, first equation.
2. Write the method in signal flow order: input -> transformation/channel/optimization ->

output -> metric. Avoid listing modules without explaining information flow.

1. Add a parameter table for experiments and shared settings. Put repeated constants there,

not scattered through prose.

1. For algorithms, add an algorithm box with initialization, loop, stopping criterion, and

returned variables. Label exact, approximate, and learned steps.

1. State convergence and complexity honestly: KKT/stationary/global only when proved; complexity

per iteration plus total iteration count when applicable.

1. Flag gaps that prevent reproduction rather than filling them by guess.

Output format

1. Methods text: polished IEEE prose or LaTeX for the requested method block.
2. Reproducibility checklist: Item -> Present / missing / needs confirmation.
3. Notation and complexity: notation table and complexity statement when relevant.
4. Assumptions and boundaries: CSI/channel/scope simplifications that need support.
5. Missing inputs: exact numbers, solver settings, data splits, or hardware details the author

must provide.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: TenWalk
• Source: TenWalk/ieee-skills
• License: MIT

Install and usage instructions live in the source repository linked above.