Additional capacity required Optimum process selected, staged for build User defined build options and current/ future constraints, filter possible waste treatment processes that can be built GA All waste arisings and composition per area Separated into waste streams Treated fractions All waste from stream treated Process discarded/ residual waste fractions Optimum bred waste treatment path order Poor performing path orders removed Best performing path order selected. Outputs recorded. Future scenario data (population, GDP, facilities) used in GA to determine if there is additional capacity required Untreated Genetic Algorithm (GA) selects a sub sample of possible waste treatment path orders (Step 1) Depth first Search Algorithm

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Multiple-input multiple-output (MIMO) detection algorithms have received considerable research interest in recent years, as a result of the increasing need for high data-rate communications. Detection techniques range from the low-complexity linear detectors to the maximum likelihood detector, which scales exponentially with the number of transmit antennas. In between these two extremes are the tree search (TS) algorithms, such as the popular sphere decoder, which have emerged as attractive choices for implementing MIMO detection, due to their excellent performancecomplexity trade-offs. In this paper, we survey some of the state-of-the-art VLSI implementations of TS algorithms and compare their results using various metrics such as the throughput and power consumption. We also present notable contributions that have been made in the last three decades in implementing TS algorithms for MIMO detection, especially with respect to achieving low-complexity, highthroughput designs. Finally, a number of design considerations and trade-offs for implementing MIMO detectors in hardware are presented.

Multiple-input multiple-output (MIMO) technology is envisaged to play an important role in future wireless communications. To this end, novel algorithms and architectures are required to implement high-throughput MIMO communications at low power consumption. In this paper, we present the hardware implementation of a modified K-best algorithm combining conventional K-best detection and low-complexity successive interference cancellation at different levels of the tree search. The detector is implemented using a fully-pipelined architecture, which detects one symbol vector per clock cycle. To reduce the power consumption of the entire receiver unit, costly symbol-rate operations such as multiplication are eliminated both within and outside the detector without any impact on the performance. The hardware implementation of the modified K-best algorithm achieves area and power reductions of 16% and 38%, respectively, compared with the conventional K-best algorithm implementation, while incurring a signal-to-noise ratio penalty of 0.3 dB at the target bit error rate. Post-synthesis analysis shows that the detector achieves a throughput of 3.29 Gbps at a clock frequency of 137 MHz with a power consumption of 357 mW using a 65-nm CMOS process, which compares favourably with the state-of-the-art implementations in the literature.

Abstract-Multiple input multiple output (MIMO) technology is anticipated to play a key role in future wireless communications systems. However, one of the main challenges of MIMO technology is the high complexity of the signal detection, which results in a high power consumption at the MIMO receiver. In this paper, we present the hardware implementation of a K-best detector based on a single-stage architecture, targeted at low-rate and lowpower applications. To achieve a low complexity, we optimise the sorting stage of the detector by systematically eliminating redundant comparators. Furthermore, the sorter incorporates different merge algorithms at selected stages in order to reduce the total comparator count. For a 64-QAM 4 × 4 MIMO system, the detector achieves a power consumption of 34 mW using the STMicroelectronics 65 nm CMOS library, which compares favourably with similar works from the literature.