Konstantinos Nikitopoulos

Exact Max-Log MAP Soft-Output Sphere Decoding via Approximate Schnorr–Euchner Enumeration

The complexity gains of sphere decoders (SDs) with Schnorr-Euchner enumeration and nonconstant amplitude constellations are limited by the required node ordering. Aiming at improving the implementation efficiency of SD without compromising optimality, this paper proposes a novel tree traversal for soft-output SDs providing the exact max-log MAP decoder performance. It consists of a predefined visiting order that approximates the exact Schnorr-Euchner enumeration (SEE) and a modified pruning metric that preserves the exact max-log MAP despite the approximate ordering. The proposed approach significantly improves both the computational complexity and the implementation cost of exact soft-output SDs compared with previous techniques. In particular, simulations show gains of 30%-56% in the required calculations for a 4 × 4 multiple-input multiple-output system with 16-quadrature amplitude modulation (QAM), and field-programmable gate array (FPGA) implementations show an average power reduction of 34%-50%.

Space-Time Super-Modulation and Its Application to Joint Medium Access and Rateless Transmission

We introduce the concept of Space-Time Super- Modulation according to which additional low rate and highly reliable information can be transmitted by further super-modulating blocks of traditionally modulated and space-time encoded information. This is achieved by exploiting the redundant information introduced by the space-time block codes and, specifically, by efficiently mapping transmission patterns to specific information content. It is shown that Space-Time Super-Modulation can be efficiently used in the context of machine-type communications to enable joint medium access and rateless data transmission while minimizing or even eliminating the need for transmitting preamble sequences. Compared with traditional approaches that use encoded preambles or preambles based on Zadoff-Chu sequences to transmit the signature information of transmitted packets, Space-Time Super-Modulation can achieve throughput gains of more than 35% when transmitting blocks of 200 symbols.

MultiSphere: Massively Parallel Tree Search for Large Sphere Decoders

This work introduces MultiSphere, a method to massively parallelize the tree search of large sphere decoders in a nearly-independent manner, without compromising their maximum-likelihood performance, and by keeping the overall processing complexity at the levels of highly-optimized sequential sphere decoders. MultiSphere employs a novel sphere decoder tree partitioning which can adjust to the transmission channel with a small latency overhead. It also utilizes a new method to distribute nodes to parallel sphere decoders and a new tree traversal and enumeration strategy which minimize redundant computations despite the nearly-independent parallel processing of the subtrees. For an 8x8 MIMO spatially multiplexed system with 16-QAM modulation and 32 processing elements MultiSphere can achieve a latency reduction of more than an order of magnitude, approaching the processing latency of linear detection methods, while its overall complexity can be even smaller than the complexity of well-known sequential sphere decoders. For 8x⌉8 MIMO systems, MultiSpheres sphere decoder tree partitioning method can achieve the processing latency of other partitioning schemes by using half of the processing elements. In addition, it is shown that for a multi-carrier system with 64 subcarriers, when performing sequential detection across subcarriers and using MultiSphere with 8 processing elements to parallelize detection, a smaller processing latency is achieved than when parallelizing the detection process by using a single processing element per subcarrier (64 in total).

Rateless wireless systems: Gains, approaches, and challenges

State-of-the-art channel coding schemes promise data rates close to the wireless channel capacity. However, efficient link adaptation techniques are required in order to deliver such throughputs in practice. Traditional rate adaptation schemes, which are reactive and try to “predict” the transmission mode that maximizes throughput based on “transmission quality indicators”, can be highly inefficient in an evolving wireless ecosystem where transmission can become increasingly dynamic and unpredictable. In such scenarios, “rateless” link adaptation can be highly beneficial. Here, we compare popular rateless approaches in terms of gains and practicality in both traditional and more challenging operating scenarios. We also discuss challenges that need to be addressed to make such systems practical for future wireless communication systems.

Space-Time Super-Modulation: Concept, Design Rules, and Its Application to Joint Medium Access and Rateless Transmission

We introduce the concept of space-time super-modulation according to which additional low-rate and highly reliable information can be transmitted on top of traditionally modulated and space-time encoded information, without increasing the transmitted block length or degrading their error-rate performance. This is achieved by exploiting the temporal redundancy introduced by the space-time block codes and, specifically, by efficiently mapping transmission patterns to specific information content. We show that space-time super-modulation can be efficiently used in the context of machine-type communications to enable one-shot grant-free joint medium access and rateless data transmission while reducing or even eliminating the need for transmitting preamble sequences. As a result, compared with traditional approaches that use correlatable preamble sequences or encoded preambles to transmit the signature information of transmitted packets, space-time super-modulation can achieve significant throughput gains. For example, we show up to 35% throughput gains from the second best examined preamble-based scheme when transmitting blocks of 200 bits.