{"id":"eeb5c902-5bd6-46c8-8afb-2af2de42237a","arxiv_id":"2509.02352","paper_version":1,"verdict":"CONDITIONAL","confidence":"MODERATE","novelty_score":3.0,"correctness_risk":"medium","formal_verification":"none","parameter_count":4,"one_line_summary":"A tutorial that classifies the five interference types in integrated sensing and communication (ISAC) and argues, with simulations, that RSMA outperforms OMA, SDMA, and NOMA in managing them.","lead":"This tutorial examines how different wireless multiple access schemes, which divide time, frequency, space, or power among users, can manage the interference that arises when a single 6G network must both communicate and sense its surroundings. It compares four schemes and argues that rate splitting offers the most flexible interference control across all integration levels.","discovery_kind":"review","skeptic_critique":{"model":"deepseek-v4-flash","headline":"The 'RSMA consistently best' claim rests on a comparison that fixes NOMA's decoding order and omits radar-sequence-enabled designs; both are acknowledged limitations in Sec. VII-C, and either could erode the headline.","rationale":"The reader's weakest assumption identifies the same protocol issue, and I agree with the conditional verdict. The strongest claim is not a theorem; it is the outcome of a specific simulation protocol. For that outcome to support 'consistently best', each MA scheme must be given its best or at least comparably optimized implementation. NOMA is the clear outlier: its decoding order is fixed while RSMA/SDMA precoders and common-rate allocations are optimized. The paper itself says decoding order has 'vital impact' in Sec. IV-B, so the fixed ascending-strength order in Sec. VII-C is not a neutral simplification. In overloaded cases with non-aligned channels, even a modest order suboptimality can depress NOMA's MFR/WSR substantially; Fig. 8 already shows NOMA losing to SDMA in O-ISAC, which is surprising and suggests the baseline is weak. Similarly, radar-sequence-enabled designs are part of the ISAC waveform space developed in Secs. II and IV; omitting them in the comparison means the test does not cover the full design space the paper itself describes. The manuscript flags both limitations, which is honest, but honesty does not make the comparative conclusion robust. The tutorial's expository value—taxonomy, system models, MA-by-MA review—is independent and should not be rejected; but the flagship numerical comparison should be treated as conditional until the baseline is made fair and the design space is complete. The concrete test above would settle the question. I therefore leave the reader's CONDITIONAL verdict unchanged.","tokens_in":46080,"tokens_out":5342,"duration_ms":65082,"concrete_test":"Recompute the Sec. VII-C comparison for Fig. 8 (NT=3, K=4, overloaded) and Fig. 10 (multi-target Q=1,2,3) under a revised protocol: (i) optimize NOMA over all K! decoding orders using the same SCA machinery, taking the best per channel realization; (ii) include radar-sequence-enabled with SIC (Pr>0, eta_r=0) for SDMA, NOMA, and RSMA, with the CRB constraint (21b) evaluated on the full transmit covariance. If RSMA's curves remain strictly above NOMA and SDMA in every panel, the headline survives; if NOMA's trade-off region shifts to overlap or cross RSMA in any panel, the 'consistently best' claim must be downgraded to regime-dependent. Releasing code/data for this sweep would make the check independently auditable.","verdict_should_be":"UNCHANGED","load_bearing_attack":"Section VII-C's central assertion that 'RSMA-assisted ISAC systems consistently deliver the best performance' is a numerical claim, so the protocol in Figs. 7-11 is load-bearing. The weakest premise is the fairness of the NOMA baseline: Section IV-B stresses that decoding order has 'vital impact' and contemplates all possible orders, but Section VII-C fixes NOMA to ascending channel strengths 'to reduce computational complexity' while RSMA and SDMA are SCA-optimized. Power-domain NOMA's rates (Eq. 5) and its SIC layers depend strongly on the order, particularly in overloaded/non-aligned channels (Figs. 8-10); fixing one order can manufacture a gap. The second loaded premise is omitting radar-sequence-enabled waveforms in the point-target scenario. This removes NOMA's information-embedding mechanism (Sec. IV-B) and the dedicated sensing beam that SDMA/RSMA can exploit, so Figs. 7-11 compare only a restricted waveform family. Both premises are explicitly acknowledged in the manuscript, not hidden. The tutorial taxonomy and the conceptual superset argument in Sec. VI-C do not depend on this comparison; but the comparative headline does. Re-running with a fair NOMA baseline and radar-sequence-enabled designs could narrow or reverse the reported gaps.","agreement_with_reader":"agree"},"referee_report":{"model":"deepseek-v4-flash","summary":"This paper is a tutorial on multiple access (MA) techniques for interference management in integrated sensing and communication (ISAC). It proposes a taxonomy of ISAC systems (O-ISAC, S-ISAC, NO-ISAC), classifies five types of interference, and reviews OMA, SDMA, NOMA, and RSMA in both downlink and uplink NO-ISAC, along with code-domain and delay-Doppler-domain MA variants. Section VII presents a numerical comparison using WSR/MFR and CRB metrics, concluding that RSMA-assisted ISAC consistently outperforms SDMA- and NOMA-assisted ISAC. The paper closes with applications, open challenges, and research directions.","tokens_in":46366,"tokens_out":5741,"duration_ms":63572,"significance":"The tutorial fills a real gap: it organizes the ISAC interference landscape from a multiple-access perspective and provides a systematic comparison of MA schemes in a common framework. The system models, SINR expressions (Eqs. (4), (5), (7)), FIM/CRB formulas, and rate definitions are standard and correctly assembled. The taxonomy of O-ISAC/S-ISAC/NO-ISAC and the five interference types is useful and well referenced. However, the numerical comparison in Section VII-C is the sole basis for the headline claim that 'RSMA consistently delivers the best performance,' and that comparison is not yet fair: the NOMA baseline is run with a fixed decoding order while RSMA/SDMA precoders are optimized, and radar-sequence-enabled designs—which Sections IV and V identify as key NOMA and RSMA mechanisms—are omitted. The conceptual contributions survive this issue, but the comparative claim is stronger than the current protocol supports.","major_comments":[{"comment":"The comparison fixes NOMA's decoding order to 'ascending channel strengths' to reduce complexity, while RSMA and SDMA precoders are optimized via the SCA algorithm from [110]. Section IV-B explicitly states that the decoding order has 'vital impact on performance enhancement' and considers all possible orders. In overloaded and non-aligned channel scenarios (Figs. 8–10), a fixed order can materially understate NOMA's achievable rates. Please re-run the comparison with an optimized or searched decoding order for NOMA, or provide evidence that the reported gap is insensitive to this choice.","section":"§VII-C, after Eq. (21)"},{"comment":"The paper states that 'the additional radar sequences are omitted in this point-target scenario' because K information streams provide enough sensing DoF. This removes the NOMA information-embedding mechanism described in §IV-B and the dedicated sensing beam available to SDMA/RSMA in §IV-A. Thus Figs. 7–11 compare only radar-sequence-disabled designs and cannot support the unqualified claim that 'RSMA-assisted ISAC systems consistently deliver the best performance compared to SDMA and NOMA-assisted ones.' Either include radar-sequence-enabled variants (with and without SIC) for all schemes, or explicitly restrict the claim to radar-sequence-disabled point-target scenarios.","section":"§VII-C, radar-sequence omission"},{"comment":"The SCA algorithm from [110] is used 'directly' for all three MA schemes, but the paper does not specify how the NOMA decoding-order constraint is incorporated into the optimization, nor the initialization, convergence tolerance, or number of iterations. Because the numerical conclusion is load-bearing, these implementation details are necessary for reproducibility and for confidence that the comparison is not an artifact of tuning. Please provide the full algorithm specification or a link to reproducible code.","section":"§VII-C, algorithm implementation"}],"minor_comments":[{"comment":"Typo: 'momo-static' should be 'mono-static'.","section":"§VII-C opening"},{"comment":"Typo: 'roubtness' should be 'robustness'.","section":"§VI-B"},{"comment":"Typo: 'rader-sequence-enabled' should be 'radar-sequence-enabled'.","section":"§IV-A"},{"comment":"Minor language: 'quests for' should be 'requires' or 'calls for'.","section":"§IV-B"},{"comment":"The text says RSMA 'consistently' achieves the best performance, but Fig. 7 and the surrounding discussion show SDMA achieving comparable MFR in the communication-prior regime. Consider using 'never worse than' or 'achieves the best trade-off region' to be precise.","section":"§VII-C, Figs. 7–11"}],"recommendation":"major_revision","confidential_remarks":"The numerical comparison in Section VII-C is the only place where the paper claims empirical superiority of RSMA, and the algorithm is taken from [110], which is a co-authored paper. I am not suggesting misconduct, but this makes it especially important that the protocol be seen as fair to all baselines. The two acknowledged choices—fixed NOMA decoding order and omission of radar-sequence-enabled designs—are exactly the choices that can inflate the reported RSMA advantage. If the authors can re-run the comparison under fairer conditions, or clearly restrict the claim, the paper will be much stronger."},"author_rebuttal":null,"desk_editor":{"model":"deepseek-v4-flash","letter":"Colleague, here's my read. The paper is a tutorial, and its genuine contribution is scope: a five-type interference taxonomy (clutter, self, inter-target, inter-user, inter-functionality), a clean O/S/NO-ISAC integration map, and a MA-by-MA review (OMA/TDMA/OFDMA, SDMA, NOMA, RSMA, plus CD-NOMA and DD-domain) with consistent SINR/FIM/CRB expressions. That is genuinely useful, and it is the first place I know that organizes this material under one roof. The conceptual claim that RSMA's partial interference decoding is a superset of SDMA/NOMA in ISAC is presented correctly, and the caveats about NOMA's sensitivity to decoding order are actually in the text (Section IV-B).\n\nThe soft spot is Section VII-C. The numerical comparison that produces 'RSMA consistently best' uses the SCA algorithm from the authors' own [110], fixes NOMA to ascending channel strengths 'to reduce computational complexity,' and omits radar-sequence-enabled waveforms in the point-target scenario—so NOMA's information-embedding mechanism and the dedicated sensing beam are off the table. These limitations are acknowledged in the text, not hidden, but they are load-bearing for the headline. I don't think this is fatal; the tutorial's expository value doesn't depend on the comparison. But as a comparative claim, it is not yet convincing. Shipping code, sweeping over NOMA decoding orders, and including radar-sequence-enabled designs would address it.\n\nThe math in the expository sections is standard and correctly assembled. The citation pattern is heavy on the authors' own RSMA-ISAC work, but that's expected in a tutorial authored by the people who built that line; it becomes a problem only when the comparative experiment is not externally reproducible, which is the case here.\n\nWho gets value: graduate students and researchers entering ISAC or MA literature who want a structured map and a reference list. Deserves a serious referee—revision should focus on the comparison protocol or on reframing the headline as illustrating the authors' framework rather than establishing a general result. My verdict: accept after major revision, or accept the tutorial part and move the comparison to a clearly labeled case study.","headline":"A useful tutorial on MA-ISAC whose comparative headline ('RSMA consistently best') rests on a simulation protocol that handicaps NOMA and omits radar-sequence-enabled designs; the expository body stands on its own.","tokens_in":46924,"tokens_out":1898,"would_cite":true,"duration_ms":21617,"reading_group":"maybe","serious_thinker":"yes","would_accept_peer_review":true},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"deepseek-v4-flash","headline":"Rate-splitting multiple access is the key to managing interference in integrated sensing and communication (ISAC), delivering the best communication–sensing trade-offs while serving as a framework that contains SDMA and NOMA.","keywords":["integrated sensing and communication (ISAC)","multiple access (MA)","rate-splitting multiple access (RSMA)","non-orthogonal multiple access (NOMA)","interference management","dual-functional waveform design","6G networks","Cramér–Rao bound"],"falsifier":"Re-run the WSR/CRB and MFR/CRB trade-off optimizations with NOMA's decoding order jointly optimized (or exhaustively searched) and with information-embedded radar sequences enabled, in the same overloaded and multi-target settings of Figs. 8–10; if NOMA-assisted or SDMA-assisted NO-ISAC matches or exceeds RSMA in any of those regimes, the claim that RSMA 'consistently' delivers the best performance is refuted for that regime.","tokens_in":1983,"feed_emoji":"📡","tokens_out":2138,"duration_ms":66364,"temperature":0.7,"pith_summary":"This tutorial organizes integrated sensing and communication (ISAC) around multiple access (MA) techniques, arguing that the five interference types in ISAC—clutter, self-interference, inter-target, inter-user, and inter-functionality—are best managed by choosing how much interference to avoid, treat as noise, or decode, which is exactly what MA schemes do. The paper walks through OMA-assisted orthogonal ISAC, SDMA/NOMA/RSMA-assisted non-orthogonal ISAC in downlink and uplink, and code-domain and delay-Doppler-domain variants, and shows numerically that RSMA-assisted ISAC delivers the best communication–sensing trade-offs in the scenarios tested. The reason to care: ISAC is a likely 6G feature, and if RSMA indeed unifies the other schemes (reducing to SDMA or NOMA by switching streams off) while its common stream doubles as a radar waveform, then a single transceiver design could serve both functionalities without dedicated radar sequences. The paper frames RSMA as the seed of a unified MA (UMA) framework for future ISAC systems.","feed_headline":"Rate-splitting outdoes SDMA and NOMA in sensing-plus-communication","feed_subtitle":"A tutorial shows the common-stream multiple access scheme beats SDMA and NOMA while doubling as a radar waveform.","key_machinery":"The common stream of one-layer RSMA: each user's message is split into a common sub-message and a private sub-message; a single common stream is jointly encoded and decoded by every user before SIC removes it, while private streams are decoded only by their intended users with residual interference treated as noise. In an ISAC transmitter this same common stream plays three roles at once—managing inter-user interference, absorbing sensing-to-communication interference that would otherwise come from dedicated radar sequences, and contributing to the transmit beampattern that radar needs—so the precoder can be optimized jointly for communication rate and sensing Cramér–Rao bound. RSMA's status","core_discovery":"On the paper's own terms, the central claim is that multiple access techniques are the right lens for ISAC interference management, and among them RSMA is the strongest: in the simulation study of Section VII-C, RSMA-assisted ISAC consistently yields the best weighted-sum-rate and max-min-fairness versus Cramér–Rao-bound trade-offs relative to SDMA- and NOMA-assisted ISAC, in both underloaded and overloaded settings and with one or multiple sensing targets. The reason offered is that RSMA splits each user message into a common part and a private part: the common stream is decoded by all users (so part of the interference is decoded, part is treated as noise), and in ISAC that same common str","pith_inferences":["The reported RSMA advantage could narrow under a fully fair comparison: the simulation hands NOMA a fixed decoding order (ascending channel strengths) while RSMA and SDMA precoders are fully optimized by SCA, and omits radar-sequence-enabled designs in which NOMA could embed information in the sensing waveform; optimizing those degrees of freedom is a direct way to test how much of the gap is intr","RSMA's advantage should be largest at intermediate interference levels—where neither treating interference as noise nor decoding it entirely is optimal—so simulations sweeping channel correlation and SINR continuously would map exactly where the gain lives.","If the common stream doubles as a sensing waveform, then the rate carried by the common stream is tied to radar beampattern quality; jointly optimizing common-rate allocation and beampattern MSE could open a trade-off axis the paper describes but does not fully explore.","The UMA argument implies that unifying code-domain NOMA (SCMA/LDS-CDMA) with RSMA remains an open problem, so a natural next step is a scheme whose sparse codewords are also rate-split streams."],"forward_implications":["RSMA-assisted ISAC can serve as a single flexible framework: switching off the common stream recovers SDMA, and pushing toward full interference decoding approaches NOMA, so one precoding design covers the whole range of interference levels.","The common stream can be shaped to meet radar beampattern requirements, meaning dedicated radar sequences may become unnecessary, simplifying the ISAC transmitter.","RSMA-assisted NO-ISAC supports overloaded networks (more users than transmit antennas) and can sense more targets without sacrificing communication QoS, as shown in the multi-target simulations.","RSMA's partial-decoding strategy remains beneficial at medium interference levels, where treating interference purely as noise (SDMA) or decoding it fully (NOMA) is suboptimal.","The comparisons of Figs. 7–11 imply that OMA-assisted O-ISAC, despite its simplicity and low interference, falls behind non-orthogonal designs in both spectral efficiency and sensing accuracy."],"supporting_citations":[{"why":"Supplies the SCA-based optimization algorithm used for the Section VII-C performance comparison and the multi-user multi-target RSMA design it extends.","marker":"[110]"},{"why":"Defines the RSMA-ISAC framework (rate-splitting for 6G, part II) and the WSR/MFR-with-CRB trade-off formulation adopted in problem (21).","marker":"[15]"},{"why":"Introduces RSMA for multi-antenna joint radar and communications, providing the common-stream-as-sensing-waveform idea and the beampattern MSE metric.","marker":"[14]"},{"why":"Provides the NOMA-ISAC perspective the paper contrasts with, including sensing targets as virtual users and information embedding into radar sequences.","marker":"[16]"},{"why":"Surveys RSMA fundamentals and establishes the superset relation (reducing to SDMA and NOMA by stream switching) that underlies the unified-MA argument.","marker":"[49]"},{"why":"Underpins the claimed NOMA degrees-of-freedom loss in underloaded multi-antenna networks, used to explain NOMA's worse trade-offs.","marker":"[51]"},{"why":"Shows RSMA bridging, generalizing, and outperforming SDMA and NOMA in communication-only systems, the template for the ISAC claims.","marker":"[52]"},{"why":"Describes the radar-sequence-enabled waveform design with SIC, the SDMA-ISAC baseline used in the transmitter models of Section IV.","marker":"[74]"},{"why":"Supports the radar-sequence-disabled design and the rank/DoF limitation of using only information signals for sensing.","marker":"[75]"},{"why":"Introduces the semi-ISAC (S-ISAC) concept and the OMA-to-NOMA integration-level framing used to classify ISAC systems.","marker":"[17]"}],"fun_headline_variants":["RSMA outmatches SDMA and NOMA in ISAC","Rate-splitting multiple access excels in ISAC","MA perspective solves ISAC interference","For ISAC, RSMA outperforms SDMA and NOMA","Tutorial: RSMA top choice for ISAC interference"],"cache_read_input_tokens":48512,"weakest_assumption_plain":"The comparative claim rests on the simulation protocol of Section VII-C, where NOMA is assigned a fixed decoding order (ascending channel strengths) while RSMA and SDMA precoders are fully optimized, and where additional radar sequences are omitted in the point-target scenario; if NOMA received its optimal decoding order and radar-sequence-based mechanisms were included, the reported RSMA advantage could shrink substantially.","fun_headline_variants_meta":{"raw":{"variants":["RSMA outmatches SDMA and NOMA in ISAC","Rate-splitting multiple access excels in ISAC","MA perspective solves ISAC interference","For ISAC, RSMA outperforms SDMA and NOMA","Tutorial: RSMA top choice for ISAC interference"]},"model":"deepseek-v4-flash","effort":"low","cost_usd":0.000756,"raw_usage":{"total_tokens":3241,"prompt_tokens":829,"completion_tokens":2412,"prompt_tokens_details":{"cached_tokens":256},"prompt_cache_hit_tokens":256,"prompt_cache_miss_tokens":573,"completion_tokens_details":{"reasoning_tokens":2344}},"tokens_in":573,"tokens_out":2412,"duration_ms":21190,"temperature":1.0,"reasoning_tokens":2344,"cache_read_input_tokens":256,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-08-05T11:35:40.536714+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":"Re-run the WSR/CRB and MFR/CRB trade-off optimizations with NOMA's decoding order jointly optimized (or exhaustively searched) and with information-embedded radar sequences enabled, in the same overloaded and multi-target settings of Figs. 8–10; if NOMA-assisted or SDMA-assisted NO-ISAC matches or exceeds RSMA in any of those regimes, the claim that RSMA 'consistently' delivers the best performance is refuted for that regime.","supporting_citations":[{"cited_title":"Rate-splitting multiple access for simultaneous multi- user communication and multi-target sensing,","cited_arxiv_id":null,"evidence_quote":"Supplies the SCA-based optimization algorithm used for the Section VII-C performance comparison and the multi-user multi-target RSMA design it extends."}],"review_version":1}