Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

Iterative multi-user detection for OFDM using biased mutation assisted genetic algorithms

Space Division Multiple Access (SDMA) aided Orthogonal Frequency Division Multiplexing (OFDM) systems assisted by efficient Multi-User Detection (MUD) techniques have recently attracted intensive research interests. As expected, Maximum Likelihood (ML) detection was found to attain the best performance, although this was achieved at the cost of a high computational complexity. Forward Error Correction (FEC) schemes such as Turbo Trellis Coded Modulation (TTCM) can be efficiently amalgamated with SDMA-OFDM systems for the sake of improving the achievable performance without bandwidth expansion. In this contribution, a MMSE-aided Iterative GA (IGA) MUD is proposed for employment in a TTCM-assisted SDMA-OFDM system, which is capable of achieving a similar performance to that attained by its optimum ML-aided counterpart at a significantly lower complexity, especially at high user loads. Moreover, when the proposed novel Biased Q-function Based Mutation (BQM) scheme is employed, the IGA-aided system’s performance can be further improved by achieving an Eb/N0 gain of about 6dB in comparison to the TTCM-aided MMSE-SDMA-OFDM benchmarker system both in low- and high-throughput modem scenarios, respectively, while still maintaining a modest complexity

Multi-agent simulation: new approaches to exploring space-time dynamics in GIS

As part of the long term quest to develop more disaggregate, temporally dynamic models of spatial behaviour, micro-simulation has evolved to the point where the actions of many individuals can be computed. These multi-agent systems/simulation(MAS) models are a consequence of much better micro data, more powerful and user-friendly computer environments often based on parallel processing, and the generally recognised need in spatial science for modelling temporal process. In this paper, we develop a series of multi-agent models which operate in cellular space.These demonstrate the well-known principle that local action can give rise to global pattern but also how such pattern emerges as the consequence of positive feedback and learned behaviour. We first summarise the way cellular representation is important in adding new process functionality to GIS, and the way this is effected through ideas from cellular automata (CA) modelling. We then outline the key ideas of multi-agent simulation and this sets the scene for three applications to problems involving the use of agents to explore geographic space. We first illustrate how agents can be programmed to search route networks, finding shortest routes in adhoc as well as structured ways equivalent to the operation of the Bellman-Dijkstra algorithm. We then demonstrate how the agent-based approach can be used to simulate the dynamics of water flow, implying that such models can be used to effectively model the evolution of river systems. Finally we show how agents can detect the geometric properties of space, generating powerful results that are notpossible using conventional geometry, and we illustrate these ideas by computing the visual fields or isovists associated with different viewpoints within the Tate Gallery.Our forays into MAS are all based on developing reactive agent models with minimal interaction and we conclude with suggestions for how these models might incorporate cognition, planning, and stronger positive feedbacks between agents

Genetically Enhanced TTCM Assisted MMSE Multi-user Detection for SDMA-OFDM

Space Division Multiple Access (SDMA) aided Orthogonal Frequency Division Multiplexing (OFDM) systems assisted by efficient Multi-User Detection (MUD) techniques have recently attracted intensive research interests. The Maximum Likelihood Detection (MLD) arrangement was found to attain the best performance, although this was achieved at the cost of a computational complexity, which increases exponentially both with the number of users and with the number of bits per symbol transmitted by higher-order modulation schemes. By contrast, the Minimum Mean-Square Error (MMSE) SDMA-MUD exhibits a lower complexity at the cost of a performance loss. Forward Error Correction (FEC) schemes such as Turbo Trellis Coded Modulation (TTCM) may be efficiently amalgamated with SDMA-OFDM systems for the sake of improving the achievable performance. Genetic Algorithm (GA) based multiuser detection techniques have been shown to provide a good performance in MUD-aided Code Division Multiple Access (CDMA) systems. In this contribution a GA-aided MMSE MUD is proposed for employment in a TTCM-assisted SDMA-OFDM system, which is capable of achieving a similar performance to that attained by its MLD-aided counterpart at a significantly lower complexity, especially at high user loads

Multiuser MIMO-OFDM Systems using Subcarrier Hopping

Recently space division multiple access (SDMA) assisted multiple-input–multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems invoking multiuser detection (MUD) techniques have attracted substantial research interest, which is capable of exploiting both transmitter multiplexing gain and receiver diversity gain. A new scheme referred to here as slowsubcarrierhopping (SSCH) assisted multiuser SDMA-OFDM, is proposed. It is shown that, with the aid of the so-called uniform SSCH (USSCH) pattern, the multiuser interference (MUI) experienced by the high-throughput SDMA-OFDM system can be effectively suppressed, resulting in a significant performance improvement. In the investigations conducted, the proposed USSCH-aided SDMA-OFDM system was capable of outperforming a range of SDMA-OFDM systems considered, including the conventional SDMA-OFDM system dispensing with the employment of frequency-hopping techniques. For example, at an Eb/N0 value of 12 dB, the proposed USSCH/SDMA-OFDM system reduced the bit error ratio (BER) by about three orders of magnitude, in comparison to the conventional SDMA-OFDM system, while maintaining a similar computational complexity

Particle-Number-Conserving Bogoliubov Approximation for Bose-Einstein Condensates Using Extended Catalytic States

We encode the many-body wavefunction of a Bose-Einstein condensate (BEC) in the $N$-particle sector of an extended catalytic state. This catalytic state is a coherent state for the condensate mode and an arbitrary state for the modes orthogonal to the condensate mode. Going to a time-dependent interaction picture where the state of the condensate mode is displaced to the vacuum, we can organize the effective Hamiltonian by powers of ${N}^{-1/2}$. Requiring the terms of order ${N}^{1/2}$ to vanish gives the Gross-Pitaevskii equation. Going to the next order, $N^0$, we derive equations for the number-conserving Bogoliubov approximation, first given by Castin and Dum [Phys. Rev. A $\textbf{57}$, 3008 (1998)]. In contrast to other approaches, ours is well suited to calculating the state evolution in the Schr\"{o}dinger picture; moreover, it is straightforward to generalize our method to multi-component BECs and to higher-order corrections.Comment: 29 pages, 1 figur

Design of Power-Splitter With Selectable Splitting-Ratio Using Angled and Cascaded MMI-Coupler

A concept of power splitter with selectable splitting-ratios is proposed based on two multimode interference (MMI) sections connected by a phase-shifting region, in which phase-matching conditions can be fulfilled by using a simple angled section or alternatively using matched phase-shifters. The design example of an asymmetrical splitter (10 : 90) is optimized by using the transfer matrix method and three-dimensional full-vectorial beam propagation method. The numerical results reveal that a simple 1.2° angled section can yield a 10 : 90 splitter with an insertion loss of 0.74 dB and a total length of 192 μm. It is also shown that, for the cascaded MMI couplers based splitter, a more compact length of 58 μm with a lower insertion loss of 0.41 dB can be achieved. The fabrication tolerances are also investigated for the proposed asymmetrical power splitter