{"id":"53fce75a-17d1-401e-ac69-4a4f229d4149","arxiv_id":"2606.03035","paper_version":1,"verdict":"UNVERDICTED","confidence":"LOW","novelty_score":5.0,"correctness_risk":"unknown","formal_verification":"none","parameter_count":1,"one_line_summary":"RA-assisted NOMA can require more power than TDMA for symmetric users but shows better robustness and efficiency in asymmetric deployments.","lead":"This preprint compares NOMA and OMA in rotatable antenna systems for minimizing transmit power under rate and rotation constraints via PSO angle optimization. A smart generalist might read it to understand when reconfigurable antennas favor one multiple access scheme over another in wireless networks.","discovery_kind":"new_application","skeptic_critique":{"model":"grok-4.3","headline":"PSO heuristic for non-convex rotational-angle optimization lacks global optimality guarantee, weakening simulation claims","rationale":"The reader's weakest assumption directly identifies the simulation reliability issue. Because all quantitative claims derive from the same PSO runs and the problem is explicitly non-convex, this is the single most load-bearing point; other elements (rate constraints, NOMA/OMA formulation) are standard and not the source of uncertainty. No independent verification (e.g., machine-checked bounds or reproducible code) is mentioned, so the concern stands.","tokens_in":1675,"tokens_out":352,"duration_ms":10865,"concrete_test":"For 20 random channel realizations, replace PSO with a uniform grid search over the rotational angle (step size 0.5°) within the feasible range and recompute the minimum powers; if grid-search powers are >10% lower or change the NOMA-TDMA ordering in >30% of symmetric cases, the simulation conclusions are unreliable.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The paper's central claims (RA-assisted power reduction vs fixed antennas; NOMA vs TDMA ordering in symmetric vs asymmetric cases) are obtained exclusively from PSO solutions to the non-convex power-minimization problem with rotational-range constraints. PSO is a stochastic heuristic without convergence guarantees to the global optimum; local minima can produce suboptimal angles. If a better angle exists, the reported transmit powers would be higher than necessary, potentially reversing the NOMA/TDMA performance ordering or shrinking the claimed gains over fixed-antenna baselines. No analytical bound, exhaustive verification, or alternative solver (e.g., grid search, gradient-based with multiple starts) is indicated in the abstract to confirm PSO quality.","agreement_with_reader":"agree"},"referee_report":{"model":"grok-4.3","summary":"The manuscript compares rotatable-antenna (RA) assisted NOMA and OMA (TDMA) schemes for transmit-power minimization subject to rotational-range and per-user rate constraints. A PSO heuristic is used to optimize the antenna rotation angle in the resulting non-convex problem; simulations are reported to show that RA yields substantial power savings relative to fixed-antenna baselines, that RA-NOMA can require more power than TDMA under symmetric user placements, and that RA-NOMA is more robust under asymmetric placements.","tokens_in":1810,"tokens_out":538,"duration_ms":17261,"significance":"If the reported performance ordering is robust to the choice of optimizer, the work supplies a concrete, deployment-relevant insight: user geometry should influence the choice between NOMA and OMA when rotatable antennas are available. The explicit comparison of the two multiple-access schemes under the same RA hardware constraint is a useful contribution to the emerging RA literature.","major_comments":[{"comment":"The central performance claims (RA power reduction, NOMA-vs-TDMA ordering in symmetric vs. asymmetric cases) rest exclusively on the solutions returned by the PSO procedure described in the optimization section. Because PSO is a stochastic heuristic without global-optimality guarantees, and because no verification (multiple random restarts, grid search on a discretized angle set, or comparison against an alternative solver) is reported, it is possible that superior rotation angles exist that would alter the reported power values and potentially reverse the NOMA/TDMA ordering. This issue is load-bearing for every quantitative conclusion in the letter.","section":"optimization section / PSO algorithm description"},{"comment":"No sensitivity analysis or error bars are provided for the PSO runs. Consequently it is impossible to assess whether the observed performance gaps are statistically significant or merely artifacts of particular PSO realizations.","section":"simulation results section"}],"minor_comments":[{"comment":"The abstract states that RA-assisted NOMA “may perform worse than TDMA” in symmetric deployments; the corresponding simulation figure or table should be referenced so readers can immediately locate the supporting data.","section":"abstract"},{"comment":"Notation for the rotational angle, the feasible interval, and the channel gains should be introduced once in the system-model section and used consistently thereafter.","section":"system model"}],"recommendation":"major_revision","confidential_remarks":"The manuscript is simulation-driven and contains no information-theoretic bounds or closed-form results; this may place it at the margin of a pure cs.IT venue, though the topic is within scope."},"author_rebuttal":{"model":"grok-4.3","summary":"We thank the referee for the constructive comments on the optimization reliability and simulation analysis. We address each point below and will incorporate the suggested verifications in the revised manuscript.","responses":[{"response":"We agree that PSO, as a stochastic heuristic, lacks global optimality guarantees and that the absence of verification is a limitation. In the revised version we will add: (i) results from 100 independent PSO runs with varied random seeds, retaining the best objective value per instance; (ii) a grid-search benchmark over a 0.1° discretization of the feasible rotation interval; and (iii) a brief comparison with a derivative-free alternative (e.g., Nelder-Mead) on selected instances. These additions will confirm that the reported power values and the NOMA/TDMA ordering under symmetric versus asymmetric geometries remain consistent.","revision_made":"yes","referee_comment":"[optimization section / PSO algorithm description] The central performance claims (RA power reduction, NOMA-vs-TDMA ordering in symmetric vs. asymmetric cases) rest exclusively on the solutions returned by the PSO procedure described in the optimization section. Because PSO is a stochastic heuristic without global-optimality guarantees, and because no verification (multiple random restarts, grid search on a discretized angle set, or comparison against an alternative solver) is reported, it is possible that superior rotation angles exist that would alter the reported power values and potentially reverse the NOMA/TDMA ordering. This issue is load-bearing for every quantitative conclusion in the letter."},{"response":"We accept this observation. The revised manuscript will include, for every plotted point, the mean and standard deviation of the minimized transmit power obtained across the multiple PSO runs, together with error bars in all figures. This will allow readers to judge the statistical significance of the gaps between RA-NOMA and RA-TDMA.","revision_made":"yes","referee_comment":"[simulation results section] No sensitivity analysis or error bars are provided for the PSO runs. Consequently it is impossible to assess whether the observed performance gaps are statistically significant or merely artifacts of particular PSO realizations."}],"tokens_in":1331,"tokens_out":455,"duration_ms":18372,"standing_objections":[]},"desk_editor":{"model":"grok-4.3","letter":"The paper fills a narrow gap by comparing NOMA and OMA under rotatable antennas for power minimization. The abstract notes the relative advantage was unclear, and the simulations supply one concrete ordering: RA helps versus fixed antennas, NOMA loses to TDMA when users are symmetric, and NOMA looks stronger when they are not.\n\nThe work is straightforward. It sets up the non-convex problem with rotation-range and rate constraints, then applies PSO to pick the angle. That produces the reported power numbers and the symmetric/asymmetric distinction.\n\nThe main weakness is exactly the one the stress-test flags. PSO is a stochastic heuristic with no global-optimality guarantee. The abstract gives no convergence plots, no multiple random starts, no grid-search checks, and no error bars. If a better angle exists in some runs, the claimed power savings shrink and the NOMA-versus-TDMA ordering can flip. That makes the central empirical claims provisional rather than solid.\n\nNo other red flags stand out from the given material. The citation pattern is normal for the sub-area, and the setup is standard.\n\nThis is for specialists already working on reconfigurable antennas or NOMA power control who want a quick simulation data point. It is not broad enough to change how most people think about multiple access. A serious editor should send it to review, but the referees will need to press on the optimizer quality before the ordering results can be trusted.","headline":"Simulations show RA cuts power and can make NOMA worse than TDMA in symmetric cases, but the PSO solver leaves those orderings unverified.","tokens_in":2293,"tokens_out":365,"would_cite":false,"duration_ms":10844,"reading_group":"maybe","serious_thinker":"yes","would_accept_peer_review":true},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"grok-4.3","headline":"Rotatable antennas reduce transmit power in multiple access networks, but NOMA can require more power than TDMA when users are symmetrically placed.","keywords":["rotatable antenna","NOMA","OMA","power minimization","multiple access","particle swarm optimization","transmit power","directional gain"],"falsifier":"An exhaustive search over all feasible rotational angles or a different global solver that produces a lower power value for NOMA than reported, or that shows TDMA no longer uses less power than NOMA in symmetric cases.","tokens_in":2588,"feed_emoji":"📡","tokens_out":598,"duration_ms":22962,"temperature":0.7,"pith_summary":"The paper compares non-orthogonal multiple access against orthogonal schemes such as time division when base-station antennas can rotate to change their directional gain pattern. It minimizes total transmit power while meeting each user's target rate and respecting the antenna's rotation limits. Rotation lowers the required power for both schemes relative to fixed antennas. When users have equal channel conditions, the NOMA version sometimes needs more power than time-division access. The ordering reverses in deployments where users have markedly different channel strengths.","feed_headline":"RA cuts power but NOMA loses to TDMA for symmetric users","feed_subtitle":"Rotation lowers power for both schemes; time-division access needs less power than NOMA when user channels are equal.","key_machinery":"The rotational angle of the antenna, optimized to minimize total transmit power subject to rate constraints and rotation limits.","core_discovery":"In RA-assisted communication systems, optimizing the antenna rotation angle via particle swarm optimization allows lower transmit power to satisfy user rate requirements than fixed antennas. For symmetric user deployments, the NOMA scheme may require higher power than TDMA, while in asymmetric deployments NOMA shows better performance in terms of robustness and energy efficiency.","pith_inferences":["System designers could select NOMA or TDMA based on measured user asymmetry rather than defaulting to one scheme.","Joint optimization of rotation angle with power allocation might yield further savings beyond the separate treatment used here.","Real deployments with hardware rotation limits and imperfect channel knowledge would test whether the simulated ordering holds."],"forward_implications":["RA-assisted schemes achieve lower transmit power than fixed-antenna systems.","NOMA can require more power than TDMA when users are symmetrically located.","NOMA provides better robustness and energy efficiency than TDMA in asymmetric user scenarios.","The performance advantage of NOMA or TDMA depends on the symmetry of user channel conditions."],"fun_headline_variants":["RA lowers power in NOMA and TDMA","NOMA needs more power than TDMA when using RA with symmetric users","RA-assisted NOMA underperforms TDMA in symmetric user scenarios","NOMA offers better efficiency than TDMA with RA in asymmetric settings"],"cache_read_input_tokens":2112,"weakest_assumption_plain":"The particle swarm optimization algorithm is assumed to locate a sufficiently good rotational angle that supports the claimed power-minimization performance under the non-convex problem with rotational-range constraints.","fun_headline_variants_meta":{"raw":{"variants":["RA lowers power in NOMA and TDMA","NOMA needs more power than TDMA when using RA with symmetric users","RA-assisted NOMA underperforms TDMA in symmetric user scenarios","NOMA offers better efficiency than TDMA with RA in asymmetric settings"]},"model":"grok-4.3","cost_usd":0.007837,"raw_usage":{"total_tokens":3545,"prompt_tokens":605,"num_sources_used":0,"completion_tokens":70,"cost_in_usd_ticks":78374500,"prompt_tokens_details":{"text_tokens":605,"audio_tokens":0,"image_tokens":0,"cached_tokens":256},"completion_tokens_details":{"audio_tokens":0,"reasoning_tokens":2870,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"tokens_in":605,"tokens_out":70,"duration_ms":18367,"temperature":1.0,"reasoning_tokens":2870,"cache_read_input_tokens":256,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-06-28T08:36:42.842396+00:00","model_set":{"reader":"grok-4.3"},"falsifier":"An exhaustive search over all feasible rotational angles or a different global solver that produces a lower power value for NOMA than reported, or that shows TDMA no longer uses less power than NOMA in symmetric cases.","supporting_citations":[],"review_version":1}