Rethinking the role of interference in wireless networks

Exploiting Constructive Interference for Simultaneous Wireless Information and Power Transfer in Multiuser Downlink Systems

“…The relevant works focus on exploiting the constructive superposition of useful and interfering signals, to utilise interfering signals as first explored for closed-form precoders [22]- [25]. In [26] a symbol-level precoding is introduced where the conventional optimization constraints are adapted to accommodate constructive interference for phase shift keying modulation (PSK).…”

“…However, we prove that they asymptotically converge to the optimal solution when the SINR threshold (Γ i ) and the modulation order (M ) tends to infinity. Towards this direction note that Algorithm 1 always provides equal or better bounds than the SOCP algorithm based on (25), while the solution from (38) provides a tighter LB than (35). Hence, it suffices to establish the result for (25) and (35), in order for it to hold true for Alg.…”

“…The main result is as follows: Proposition 1. The solutions of (25) and ( Proof : The proof is provided in Appendix B. Proposition 1 is important because practical systems often use a large modulation order and high SINR threshold to achieve high data rates and low outage probability, in which cases the proposed algorithms will achieve asymptotically optimal results.…”

“…The algorithm starts by solving problem (25) to obtain an initially feasible solution. Then, an iterative procedure is followed which involves linear approximation of the nonconvex terms upon derivation of y R i(τ ) and y I i(τ ) , followed by the solution of problem (29) to obtain a new approximate solution to the initial problem.…”

“…SLA is a widely used procedure in signal processing for communications that has been proven to converge to a local optimum [35]. Algorithm 1 starts from the solution of (25) and progressively improves so that its solution is at least as good as the one of (25). Hence, there is a computational complexity/solution quality tradeoff between formulation (25) and Algorithm 1 as the former has lower computational complexity, while the latter yields results closer to optimality.…”