arXiv:2611.06576v1 Announce Type: new Abstract: Wi-Fi~7 and 5G NR use constellations up to $4096$-QAM and $1024$-QAM at multi-gigabit peak rates. The MIMO detector must sustain these rates at a low cost. Linear MMSE detection meets these rates at low cost but loses several dB in SNR. $K$-Best detection recovers this loss, but its per-layer sorting grows with the modulation order and needs large sorting networks or deep pipelines at these rates. Box Decoding is a sort-free tree-search detector whose complexity does not depend on the QAM order, and its deterministic pruning keeps the cost fixed as the MIMO size grows. Single-step candidate pruning (SCP) is fully parallel but less accurate, while iterative candidate pruning (ICP) is more accurate, but its selection loop costs either throughput or area. This paper proposes Max-Min-Exchange Candidate Pruning (MMECP), which replaces the selection loop of ICP with a single max-min exchange without a feedback path and keeps \mbox{near-$K$-Best} performance. The paper also presents a VLSI architecture that represents each candidate by its integer constellation index, so that candidates and their distances are obtained by bit selection instead of operations on symbol values. A $4\times4$ detector synthesized in TSMC $16$\,nm detects one vector per cycle at $1$\,GHz for $64$- to $1024$-QAM and produces up to $40$\,Gb/s, while its gate count grows by $63\%$ over this range. Its normalized hardware efficiency is $2.3\times$, $12\times$ and $14\times$ that of the best compared hard-output detector at $64$-, $256$- and $1024$-QAM.