Fast Fluid Antenna Multiple Access Enabling Massive Connectivity

Abstract

Massive connectivity over wireless channels relies on aggressive spectrum sharing techniques. Conventionally, this may be achieved by sophisticated signal processing and optimization of applying multiple antennas and/or complex multiuser decoding at each user terminal (UT). Different from previous methods, this letter proposes a radical approach for massive connectivity, which employs fluid antenna at each UT to exploit the interference null, created naturally by multipath propagation and the randomness of UT's data, on a symbol-by-symbol basis for multiple access. The proposed fast fluid antenna multiple access (f -FAMA) system adopts a large, distributed antenna array at the base station (BS) to transmit each UT's signal from each of the BS antennas and lets each UT overcome the interference on its own using its fluid antenna. Our main contribution is a technique that estimates the best port of fluid antenna for reception at every symbol instance. The proposed approach needs only cross-correlation calculations and single-user decoding at each UT and requires no precoding at the BS. Simulation results demonstrate that for a BS with 16 antennas supporting 16 co-channel users, a multiplexing gain of 14.87 is achieved even when the channel has a strong line-of-sight (LoS) and multipath is few. The multiplexing gain can also rise to 24.36 if a 30-antenna BS is serving 30 co-channel users.

Slow Fluid Antenna Multiple Access

“…Nonetheless, (2) requires port switching on a symbolby-symbol basis which is extremely difficult to achieve. Even though reconfigurable pixels-based fluid antennas could switch ports without delay and recent work also addressed how the ratios (2) at the ports could be estimated for each symbol [19], there was still the complexity of observing a large number of signals (equalling the number of ports) at each symbol instant, which could be impractical. In [17], this approach is referred to as fast fluid antenna multiple access (f -FAMA).…”

“…With the above results, the outage probability, Prob(SIR < γ), can be evaluated by (63) (see top of next page) in which (a) uses the results (60) and ( 62), (b) moves the integration over y k inside the product, and (c) uses the fact that the total probability of a noncentral Chi-square random variable is one. Finally, the integral inside the product over y k is recognized to be of the form (19)…”

Maximizing the network outage rate for fast fluid antenna multiple access systems

“…Consequently, we have $$$$\begin{equation} k_u^*=\arg \max _k{\rm SIR}_k\equiv \arg \max _k\frac{{\left|g^{(u,u)}_k\right|}^2}{{\left|\tilde{g}^{(u)}_k\right|}^2}. \end{equation}$$$$Note that how to estimate the port SIR at each symbol itself has been addressed in [39]. Some ideas on this have also been discussed in [10].…”

“…There are two types of FAMA: (i) fast FAMA ( f -FAMA) [37][38][39] and (ii) slow FAMA (s-FAMA) [40]. For s-FAMA, the fluid antenna of each user selects the port that maximizes the average received signal-to-interference plus noise ratio (SINR) in which the averaging is taken over the transmitted data of all the users.…”

“…Despite the results in [37–40], FAMA research is still in an early stage. In particular, the SIR threshold, γ, is always fixed and arbitrarily given.…”