On DeWi Network Design Tradeoffs

Context

In our last piece, On DeWi Unit Economics, we proposed that DeWi networks are fundamentally better businesses than TradWi telco networks. Why?

DeWi token models align the incentives of landlords and networks, reducing rents in the system. In retail deployments, the “landlord” and the “network” are the same economic actor. In institutional deployments, landlords are more likely to accept revenue-share agreements because of the transparency of mining rewards earned on a property. TradWi networks run <40% cash operating margins. We think DeWi networks can reach 50–60%+.

Tokenizing spectrum licenses transforms spectrum from an unproductive asset to a productive one. Spectrum licenses make up 55% of TradWi’s productive assets ($350B+ in the US alone), yet they often sit unused on balance sheets for years while compatible equipment is deployed and new offerings are marketed. Licenses reduce TradWi networks’ productive asset turnover (a measure of capital efficiency) from 120% to 50%. We think DeWi networks can reach 70–80%+.

Back‑of‑the‑envelope: TradWi ≈ (0.5× asset turnover) × (40% operating cash flow margin) = 20% unlevered returns.
DeWi ≈ (0.75× asset turnover) × (55% operating cash flow margin) = 41% unlevered returns.

DeWi networks can generate double the returns of TradWi. DeWi can undercut incumbents by 50% and still earn higher unlevered returns. If demand for data transfer is elastic, then cutting the cost in half should grow the market significantly.

Research suggests long‑term consumers’ price elasticity for mobile voice communication is ~1.12 in developed markets and enterprises’ elasticity for public clouds is ~1.20. A price elasticity > 1 implies that a decrease in price is more than offset by increased demand, so revenue grows even as prices fall. At the range above (1.12–1.20), cutting data transfer prices in half would tap into $30–50B of latent demand for data transfer in the US (in addition to the incumbents’ $315B+ service revenues in 2021).

DeWi Layer‑1 Protocols

Layer‑1 protocols are the most asymmetric bets in crypto. As we’ve previously written, L1s sell access to one of the three digital commodities: compute, storage, bandwidth.

The winning L1 in each category needs a credible path to a monetary premium via the utility hypothesis. With a potential opportunity of $75T+ (the combined M2 of the world’s 5 largest economies), even a minuscule chance of becoming global money deserves—probabilistically—an expected value in the billions.

Today, market valuations imply roughly 1‑in‑200 odds for the store of value thesis; ~1‑in‑300 for the compute utility thesis; and ~1‑in‑13,400 for the bandwidth/storage utility thesis. We ask: is bandwidth really 100× less likely than compute or store‑of‑value?

1) Power vs Cost

To be valuable, a DeWi network must provide useful coverage. More powerful equipment usually means higher cost and operational complexity. For example, Helium/Pollen CBRS radios are 10–15× more expensive than LoRa hotspots and have ~10× smaller coverage area—but data capacity is ~10,000× higher than LoRa.

Costs are borne by miners, but protocols “pay” via slower growth and decentralization. Increasing the capital and effort required to mine shrinks the pool of potential miners and flattens growth. Tiered node classes can help—e.g., low‑cost mappers vs. indoor radios vs. outdoor radios—expanding the TAM of miners, at the expense of early‑stage complexity (validation, anti‑gaming, support, supply chain).

As networks mature, mining difficulty rises. Early miners take equity‑like risk and earn outsized rewards; later miners earn less per unit of contribution. Over time, networks tend to shift from retail to institutional miners as competition increases and economies of scale dominate.

2) Centralization vs Decentralization

DeWi networks progressively decentralize. Manufacturing is often first: Helium moved from a single vendor to 30+ approved manufacturers over ~2 years. Decentralization is gradual and doesn’t guarantee diversity or fairness; the top vendors can still concentrate share, and networks often retain some centralized controls (e.g., Helium’s Manufacturing Compliance Committee) to protect integrity.

Other areas decentralize over time: price oracles, treasury management, grants programs, and governance. Each introduces tradeoffs between speed, security, transparency, and attack surface.

3) New vs Existing Demand

Networks can pursue new markets (IoT, AVs) with less incumbent competition but uncertain size/timing, or existing markets (mobile) with huge TAM but intense competition and chicken‑and‑egg dynamics that often require partnerships.

Helium’s LoRaWAN (IoT) network has meaningful scale but modest data transfer revenues today; the cellular (indoor offload) opportunity—reselling coverage through carriers in venues such as airports, stadiums, hospitals, schools—could reach ~$10B in the US over ~5 years, though still a fraction of total telco revenues.

4) Token Dilution Now vs Later

How aggressively should networks pay miners from a fixed supply? Paying more today can accelerate build‑out (especially in retail‑driven networks) but risks downward spirals in bear markets and reduces optionality for future networks. Helium’s max supply (per HIP‑20) allocates ~62% to lifetime mining rewards; a large portion has financed LoRa build‑out, leaving less for CBRS and future subDAOs. Designs like HIP‑51/52/53 introduce subDAO tokens with bonding to HNT; whether markets price them at a premium remains to be seen.

5) Open‑Source vs Closed‑Source Mobile Core

Many DeWi networks use Magma, an open‑source mobile core (no license cost; active community), which today focuses on data and has limited interoperability with legacy telco systems. Closed‑source cores (Azure, Oracle, Rakuten, Mavenir, Nokia, Ericsson, Cisco) bring broader feature sets and integrations at the cost of vendor lock‑in and higher expense.

6) Licensed vs Unlicensed Spectrum

CBRS general‑access spectrum enables US‑only, data‑first deployments but introduces constraints (interference risks, power limits, FCC registrations). Longer‑term, tokenizing licensed spectrum could turn it into a productive asset for DeWi—combining DAO capital formation with real‑world spectrum markets.

— Sal ([email protected]) & Mahesh ([email protected])

References (selected)

• Consumer price elasticity for mobile voice (ScienceDirect)
• Enterprise compute elasticity (ResearchGate)
• HIP‑20: HNT max supply
• FreedomFi
• Federated Wireless Spectrum Exchange