Adaptive Beamforming and Adaptive Modulation-Assisted Network Performance of Multiuser Detection-Aided FDD and TDD CDMA Systems

The network performance of a frequency division duplex and time division duplex (TDD) code division multiple access (CDMA)-based system is investigated using system parameters similar to those of the Universal Mobile Telecommunication System. The new call blocking and call dropping probabilities, the probability of low-quality access, and the required average transmit power are quantified both with and without adaptive antenna arrays (AAAs), as well as when subjected to shadow fading. In some of the scenarios investigated, the system’s user capacity is doubled with the advent of adaptive antennas. The employment of adaptive modulation techniques in conjunction with AAAs resulted in further significant network capacity gains. This is particularly so in the context of TDD CDMA, where the system’s capacity becomes poor without adaptive antennas and adaptive modulation owing to the high base station (BS) to BS interference inflicted as a consequence of potentially using all time slots in both the uplink and downlink of the emerging wireless Internet. Index Terms—Adaptive beamforming, adaptive modulation, code division multiple access (CDMA) systems, Universal Mobile Telecommunication System Terrestrial Radio Access (UTRA), wireless network performance

Spatial channel characterization for smart antenna solutions in FDD wireless networks

This paper introduces a novel metric for determining the spatial decorrelation between the up- and down-link wireless bearers in frequency division duplex (FDD) networks. This metric has direct relevance to smart or adaptive antenna array base-station deployments in cellular networks, which are known to offer capacity enhancement when compared to fixed coverage solutions. In particular, the results presented were obtained from field trial measurement campaigns for both urban and rural scenarios, with the observations having a direct impact on the choice of down-link beamforming architecture in FDD applications. Further, it is shown that significant spatial decorrelation can occur in urban deployments for bearer separations as small as 5 MHz. Results are presented in terms of both instantaneous characteristics as well as time averaged estimates, thus facilitating the appraisal of smart antenna solutions in both packet and circuit switched network

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