Wireless technology is growing rapidly to realize the goal of ubiquitous connectivity, no matter where you are in the world. This white paper looks at wireless connectivity trends and design challenges, along with how wireless engineers can use MATLAB® and Simulink® to design, model, simulate, and test modern wireless networks.
Wireless communications enable high-speed internet connectivity, mobile phone calls, and Internet of Things (IoT) connections in smart factories. This ubiquitous connectivity is made possible by a wide range of wireless technologies, including global wide area networks (satellite links), cellular wide area networks (5G and 5G Advanced), local area Wi-Fi® networks, and personal area networks such as Bluetooth® and ZigBee®.
Figure 1. Ubiquitous connectivity is the goal of wireless communication, involving different wireless network types.
MATLAB and wireless communication toolboxes enable engineers to design, model, simulate, test, validate, and prototype wireless connectivity systems. Wireless engineers can use these products to generate and analyze standards-based waveforms, measure link-level performance, and create golden reference models to verify standard conformance. Development workflows include prototyping transceiver algorithms in MATLAB or in HDL, with relevant software-defined radio (SDR) platforms. Engineers can also simulate and analyze the coexistence between many wireless systems that can interfere with one another. The toolbox functions are fully customizable, enabling teams to accelerate implementations and explore the latest satellite, 5G, WLAN, and Bluetooth technologies.
In the next few sections, we will explore various ubiquitous connectivity technologies along with the relevant standards, challenges, and resources that enable engineers to model, simulate, analyze, design, and test these networks.
Cellular Connectivity (5G to 5G Advanced to 6G)
The standard body responsible for cellular mobile communications is the 3rd Generation Partnership Project (3GPP). Since the beginning of this century, 3GPP has been responsible for the standardization of 3G, 4G (i.e., LTE), 5G, and 5G Advanced systems and networks. Recently, 3GPP has embarked on standardizing 6G, the next generation of mobile communications systems.
Radiation Pattern of a Ground-based Phased Array.
5G NR is designed to support three use cases:
- Enhanced mobile broadband: delivering significantly higher data speeds and network capacity compared to the previous (LTE) generations
- Ultra-reliable low-latency communications: focusing on providing the real-time responsiveness and reliability essential for safety critical applications such as telemedicine, smart cities, and smart factories
- Massive machine-type communications: Enables large-scale IoT deployments with millions of connected devices
5G Advanced goes beyond use cases offered by 5G and includes the following use cases:
- Ubiquitous connectivity: Integration with satellite networks for global coverage uses satellites and high-altitude platforms to extend 5G coverage to remote and rural areas, oceans, and airspace.
- Integrated Sensing and Communication (ISAC): Networks can simultaneously communicate and sense their environment, offering high-accuracy localization and tracking.
- Artificial intelligence (AI) and machine learning integration: AI and machine learning are embedded throughout the network to enable dynamic resource allocation, predictive optimization, and real-time adaptability, making the wireless network more efficient.
6G systems, currently under development, will extend the capabilities of 5G Advanced. The ITU is working on the IMT-2030 document for the next generation of 6G systems, including technologies such as integrated AI and communications, ISAC, ubiquitous coverage with non-terrestrial networks (NTN), and green energy-efficient network design.
Spotlight: 5G Toolbox
Simulate 5G NR links and systems with standards-based waveforms updated with every 3GPP release. Generate waveforms, perform system-level simulations, conformance testing, and more, all from MATLAB.
5G Toolbox also supports AI-driven wireless optimization techniques and includes a 6G Exploration Library for prototyping next-generation candidate technologies.
Developing efficient 5G Advanced and 6G systems and networks is challenging and poses severe design requirements to achieve their new use cases. MATLAB and its standards-based tools, such as 5G Toolbox™, can be used to simulate at the link and system level. As 5G Toolbox keeps up with 5G standards updates in every 3GPP release, it makes the tasks of design verification and standards conformance testing easier.
"6G is exploring replacing entire blocks of the signal processing chain, such as channel estimation and equalization, with trained machine learning models."
Integrating native AI and machine learning:
- The physical layer (PHY) design must accommodate AI and machine learning to enhance performance in areas like channel estimation, beam management, and network optimization. Unlike 5G, which primarily uses AI for optimization, 6G is exploring replacing entire blocks of the signal processing chain, such as channel estimation and equalization, with trained machine learning models. This approach aims to create a fully AI-native PHY.
- Explore these concepts further by reviewing the accompanying MATLAB examples:
Enhanced and cell-free massive MIMO:
- Designing even more advanced massive MIMO systems requires managing larger antenna arrays and more complex beamforming algorithms. The PHY must handle the increased processing and signaling overhead associated with higher-dimensional antenna setups. Another exciting area of development is a cell-free architecture proposed for 6G systems, where users connect to multiple distributed access points simultaneously.
- Explore these concepts further by reviewing the accompanying MATLAB examples:
ISAC:
- ISAC systems require the PHY to support both communication and accurate sensing functions simultaneously. This means that both functions use the same waveforms, operating at the same frequency, and use the same hardware without degrading performance. ISAC is envisioned to be a core component of 6G systems, aiming to achieve centimeter-level accuracy for positioning and high-resolution environmental sensing.
- Explore these concepts further by reviewing the accompanying MATLAB examples:
"There are currently more than 8,000 communication satellites in orbit around the Earth serving applications such as TV and radio broadcasting, navigation, telemetry, imaging, and remote sensing, and that number is growing."
Satellite communications, and specifically NTNs, are emerging as important enabling technologies for ubiquitous connectivity. There are currently more than 8,000 communication satellites in orbit around the Earth serving applications such as TV and radio broadcasting, navigation, telemetry, imaging, and remote sensing, and that number is growing. Communication satellites usually fall under one of three orbital classifications: geostationary (GEO), medium Earth orbit (MEO), and low Earth orbit (LEO).
The use of LEO satellite constellations for wireless connectivity is an emerging trend. With an orbital altitude ranging from 160 to 1,000 km above the Earth’s surface, these systems are slated to provide high-speed internet connectivity anywhere on Earth. For example, the Starlink system already has thousands of satellites in orbit, with plans to launch thousands more.
Spotlight: Satellite Communications Toolbox
MathWorks' Satellite Communications Toolbox provides tools for designing, simulating, and verifying satellite communications systems, covering orbit propagation, link budget analysis, and waveform generation for standards like DVB-S2/S2X/RCS2, GPS, Galileo, NavIC, and CCSDS.
Deploying satellite communications systems is complex, costly, and risk-intensive. Key challenges exist in the areas of launch and deployment, security and resilience, economic and business models, and environmental concerns. In the following section, communication-specific challenges are presented along with relevant MATLAB examples that address their solutions:
Challenge: Mission planning and regulatory compliance
- Securing orbital slots and frequencies through ITU and national regulators
- Coordination to avoid interference with incumbent systems
MATLAB examples:
Challenge: Technical design and integration
- Link budget closure across variable atmospheric conditions, such as rain fade and scintillation, which can degrade signal strength
- Antennas must deliver high gain and precise beamforming while meeting constraints on size, weight, and power.
- Payload complexity (for example, digital processors, regenerative vs. bent-pipe architectures)
- Inter-satellite links and timing/synchronization for large constellations
MATLAB examples:
Challenge: Performance in challenging environments
- Atmospheric attenuation at higher bands (Ka, Q/V) and need for adaptive coding/modulation, uplink power control, and site diversity
- Latency constraints vs. orbit selection (LEO/MEO/GEO tradeoffs)
- Doppler and frequent handovers in LEO networks mean beam hopping and resource scheduling are vital to maintain seamless connectivity
MATLAB examples:
Figure 2. The LEO NTN satellite constellation features inter-satellite routing.
Wi-Fi is the most widely used wireless technology in the world. Wi-Fi networks provide internet connectivity in our homes, at work, and while traveling (in airports, stadiums, and other public venues). Wi-Fi networks operate by connecting user devices to an access point (AP) router based on the IEEE 802.11 family of standards. These wireless local area network (WLAN) standards specify both the PHY and Media Access Control (MAC) layers of the OSI model.
"Wi-Fi 8 (802.11bn) is designed for increased reliability, for example in manufacturing or robot-assisted surgery. Wi-Fi 7 (802.11be) provides higher speeds and uses wider frequency bandwidths."
Wi-Fi 6, 7, and 8 are among the latest WLAN technologies designed for reliable and high-speed internet connectivity.
- Wi-Fi 6 (802.11ax) provides superior performance in dense environments by employing multiple access technologies like OFDMA and MU-MIMO.
- Wi-Fi 7 (802.11be) is designed for higher speeds and uses wider frequency bandwidths (up to 320 MHz) offering peak transmission speeds of up to 46 Gbps.
- Wi-Fi 8 (IEEE 802.11bn) is being developed and will focus on prioritizing ultra-high reliability, lower latency, and consistent performance.
Developing efficient Wi-Fi systems and networks presents challenges and poses requirements for reliability, handling congestion, and coexistence with other networks. Engineers can use MATLAB to simulate many of these challenging scenarios and explore their mitigation design space.
MATLAB examples:
Challenge: Bluetooth-Wi-Fi coexistence
Bluetooth devices in the 2.4 GHz frequency band and Bluetooth Low Energy (BLE) devices at the 6 GHz band can interfere with Wi-Fi networks. Interference between Bluetooth and WLAN can be mitigated with noncollaborative and collaborative coexistence mechanisms.
- Noncollaborative coexistence mechanisms do not exchange information between two wireless networks.
- Collaborative coexistence mechanisms collaborate and exchange network-related information between two wireless networks.
MATLAB examples:
Challenge: Improving performance in congested environments
In dense environments (such as stadiums and conference centers) many devices connect to Wi-Fi networks simultaneously. This can diminish the total network capacity and overwhelm resource allocations in access points (APs). Wi-Fi 6, 7, and 8 employ several techniques borrowed from cellular mobile technology to improve performance with a higher density of users and devices:
- Orthogonal frequency division multiple access (OFDMA): Divides a channel into smaller sub-channels to service multiple devices simultaneously
- Multi-user multiple-input multiple-output (MU-MIMO): Allows an AP to send and receive data from several devices at the same time and frequency resource
- Uplink trigger-based format: Shifts the uplink traffic from a traditional Wi-Fi uncoordinated, contention-based system to a precisely coordinated, scheduled system
- Quality of Service (QoS): Prioritizes critical applications like voice and video conferencing using QoS settings
- Spatial reuse with basic service set (BSS) coloring
MATLAB examples:
Challenge: Co-channel interference
When multiple Wi-Fi stations transmit on the same frequency, co-channel interference can occur, which causes packet collisions and reduced throughputs. Wireless engineers can reduce interference by employing:
- Trigger-based uplink transmission that offers coordinated scheduling for each device
- Directional antennas (MU-MIMO) to focus on Wi-Fi signals where they are needed
- Reduced channel bandwidths
- Channel planning for non-overlapping channels in 2.4 GHz band
MATLAB examples:
Other Wi-Fi capabilities:
Wi-Fi sensing
Integration with AI
Adoption of mesh networks
Accelerating Wireless Engineering with MATLAB and Simulink
MathWorks is committed to accelerating the pace of engineering and science. For wireless engineers, MATLAB and Simulink make wireless communications designs faster and more efficient with modeling, simulation, testing, and implementation tools.
Every toolbox and product mentioned in the report is kept in compliance with the latest industry standards. Whether you’re prototyping a 6G AI-native receiver or validating a Bluetooth 6 design, MathWorks products bridge the gap between concept and hardware.
Bluetooth is a short-range wireless technology used for exchanging data between devices over short distances. The Bluetooth standard is designed by the Bluetooth Special Interest Group (Bluetooth SIG). Bluetooth 6, announced in 2024, introduced technologies such as Channel Sounding, which can provide extremely accurate range estimates between Bluetooth nodes.
Spectrum and Spectrogram of Bluetooth/WLAN Coexistence.
The Bluetooth Classic standard specifies two PHY modes: basic rate (BR) and enhanced data rate (EDR). In addition, the BLE standard focuses on applications in industries like healthcare, fitness, security, and home entertainment. Also, Bluetooth systems can perform localization using technologies like triangulation and trilateration.
The following section outlines the major challenges when deploying Bluetooth devices and networks, along with relevant MATLAB examples that address those challenges.
Challenge: Radio planning and coexistence
- The unlicensed 2.4 GHz is crowded with Wi‑Fi, microwaves, and Zigbee signals, creating interference, multipath, and duty-cycle contention.
- Adaptive frequency hopping (AFH) helps, but dense RF environments still degrade throughput, latency, and reliability.
- Antenna detuning from enclosures or human proximity can reduce range; careful RF layout, ground clearance, and tuning are essential.
MATLAB examples:
Challenge: Topology, scalability, and performance
- Classic Bluetooth (BR/EDR) piconets have limited active connections; asynchronous connection-oriented logical transport (ACL) link scheduling can become a bottleneck.
- Low energy connection limits per gateway/phone and connection interval constraints cap scale and responsiveness.
- Bluetooth mesh scales to thousands of nodes, but managed flooding increases airtime, collisions, and battery drain; careful time to live (TTL), relay, and friend/low-power-node configuration is required.
MATLAB examples:
Challenge: Localization
- Received signal strength indicator (RSSI) instability
- Angle-based requirement for antenna arrays
- Synchronization and calibration in magnitude, phase, and time
- Interference and channel availability
MATLAB examples:
Figure 3. Bluetooth Channel Sounding is used for asset tracking, showing the asset path and Bluetooth locator notes (blue and yellow triangles).
The following section outlines the major challenges in designing standards-based transceivers for wireless systems, along with relevant MATLAB examples that address these challenges.
AM/AM Characteristics of a Nonlinear Amplifier.
EVM Over Time and Frequency for an Over-the-Air 5G Waveform Capture.
Challenge: Ensuring compliance with standard protocols for system and device interoperability
- This can require algorithm designers and chip testers to obtain standards-based waveforms, both impaired and unimpaired, to test receiver designs or stimulate receiver chips.
- It can also require measurement testbenches for quantities like error vector magnitude (EVM), adjacent channel power ratio (ACPR), and packet error rate (PER).
MATLAB examples:
Challenge: Optimizing system parameters by integrating algorithms, antenna, array, and RF transceiver design choices
- This requires trade studies on array sizes, array element types, and element coupling leading to beam squinting, high power amplifier (HPA) nonlinearity limits, low noise amplifier (LNA) noise figures, and impedance mismatch levels.
- It can also require design choices on modulation schemes and error control codes.
MATLAB examples:
Challenge: Verifying the designs on hardware prototypes with automated over-the-air tests and realistic channel and impairment models
- At the early stages of design, this requires connectivity between waveform capture devices like SDRs and the software used to prototype receiver algorithms.
- In the later stages of design, this could require deployment of Hardware Description Language (HDL) code to field programmable gate arrays (FPGAs).
MATLAB examples:
Figure 4. Stages of the wireless workflow cover wireless standards, antenna-to-bits simulation, and device implementation and testing.
As the world progresses towards ubiquitous connectivity, from 5G Advanced to 6G and beyond, the convergence of cellular, satellite, Wi-Fi, and Bluetooth technologies is creating an ecosystem of unified global communication. This white paper has explored the key technologies, standards, and challenges that define this landscape, while demonstrating how MATLAB and Simulink serve as essential products for designing, simulating, and validating these complex wireless systems.
