Multicast Beamforming Techniques in Wireless Communication Systems

Multicast beamforming exploits the spatial degrees of freedom of multi-antenna transmitters to deliver common information streams simultaneously to multiple users. By shaping the transmitted wavefront through carefully designed weight vectors, beamforming achieves constructive signal combining at intended receivers while limiting interference to others. Two principal design criteria dominate the field: max-min fairness, which maximises the weakest link’s signal quality under a total power budget, and quality-of-service optimisation, which minimises transmit power subject to per-user signal-to-noise or signal-to-interference-plus-noise ratio constraints. Advanced formulations further address bandwidth efficiency by segmenting large multicast groups into smaller cohorts, integrate energy harvesting requirements for devices with simultaneous wireless information and power transfer, and incorporate satellite or cell-free deployments to extend coverage. Key challenges include imperfect channel state information, heterogeneous user demands, inter-group interference, and the computational burden of nonconvex optimisation. Recent progress leverages convex relaxations, successive approximation, and artificial-intelligence-inspired schemes to approach near-optimal solutions with reduced complexity. As 5G and beyond networks call for high-capacity, low-latency group communications—for example in live video streaming, software updates over the air and mission-critical Internet of Things—multicast beamforming emerges as a critical enabler of spectral efficiency and energy-aware service delivery.

Research from Nature Portfolio

No recent Nature Portfolio content available.

Multicast Beamforming Techniques in Wireless Communication Systems publication trend

The graph below shows the total number of articles in multicast beamforming techniques in wireless communication systems across all publications each year (not limited to Nature Index journals).

Technical terms

Beamforming: The spatial filtering of signals across multiple antennas to direct energy toward intended receivers and suppress interference.

Multicast: A communication mode in which identical data is transmitted simultaneously to a group of users rather than to each individually.

Precoding: The application of complex weight matrices at the transmitter to pre-shape signals for multiuser transmissions, often based on channel state information.

Signal-to-Interference-plus-Noise Ratio (SINR): A measure of received signal quality defined as the power of the desired signal divided by the sum of interference and noise powers.

Convex Relaxation: A mathematical technique that transforms a nonconvex optimisation problem into a convex one by relaxing certain constraints, enabling efficient solution methods.

Intelligent Reflecting Surface (IRS): A planar array of passive elements whose tunable phase shifts create controllable reflection paths to enhance wireless channel conditions.

References

1. Feasible Point Pursuit and Successive Convex Approximation for Transmit Power Minimization in SWIPT-Multigroup Multicasting Systems. IEEE Transactions on Green Communications and Networking (2021).
2. Multigroup Multicast Precoding for Energy Optimization in SWIPT Systems With Heterogeneous Users. IEEE Open Journal of the Communications Society (2019).
3. Satellite-Assisted Cell-Free Massive MIMO Systems with Multi-Group Multicast. Sensors (2021).
4. Intelligent-Reflecting-Surface-Assisted Multicasting with Joint Beamforming and Phase Adjustment. Applied Sciences (2022).
5. A Physical Layer Multicast Precoding and Grouping Scheme for Bandwidth Minimization. IEEE Access (2021).
6. Multi-Group Multicast Beamforming by Superiorized Projections Onto Convex Sets. IEEE Transactions on Signal Processing (2021).