Communication baseband workloads such as covariance estimation, synchronization and reduction operations exhibit substantial data-level parallelism. The RISC-V Vector Extension (RVV) introduces vector-length agnostic (VLA) execution, enabling scalable vector implementations independent of a fixed hardware width. In this work, we explore architectural scalability trade-offs of a configurable RVV-based vector processor across VLEN, lane count, and lane width. Using representative communication kernels and synthesis with the predictive ASAP7 PDK, we analyze architectural scaling behavior and the interaction between cycle reduction and frequency degradation. While increasing VLEN reduces cycle counts, critical-path growth and bandwidth imbalance introduce a parallelism–frequency trade-off that yields kernel-dependent optimal configurations. We further demonstrate how a lightweight custom vector complex multiplication instruction improves efficiency for covariance-based workloads. The results highlight the importance of balanced compute–memory design for practical and physically realizable RVV implementations.