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Base station cooperation can exploit knowledge of the users' channel state information (CSI) at the transmitters to manage co-channel interference. Users have to feedback CSI of the desired and interfering channels using finite-bandwidth backhaul links. Existing codebook designs for single-cell limited feedback can be used for multicell cooperation by partitioning the available feedback resources between the multiple channels. In this paper, a new feedback-bit allocation strategy is proposed, as a function of the delays in the communication links and received signal strengths in the downlink. Channel temporal correlation is modeled as a function of delay using the Gauss-Markov model. Closed-form expressions for bit partitions are derived to allocate more bits to quantize the stronger channels with smaller delays and fewer bits to weaker channels with larger delays, assuming random vector quantization. Cellular network simulations are used to show that the algorithm presented in the paper yields higher sum-rates than the equal-bit allocation technique. [ABSTRACT FROM PUBLISHER]

Recently, an adaptive intercell interference (ICI) mitigation technique has been proposed for downlink cellular systems as a means to increase throughput with low system complexity. However, in the prior work, the issue of intercell user scheduling has not been considered. In this paper, we study multiple-input–single-output (MISO) downlink cellular systems that jointly design adaptive ICI cancelation (ICIC) and intercell user scheduling assuming that partial channel state information (CSI) is shared among base stations (BSs). Since the optimal solution would require high complexity, we investigate a new low-complexity algorithm that selects the best users and their beamforming strategies in terms of maximizing the weighted sum rate (WSR). To this end, we first develop a simple threshold criterion for each user to decide the preferred beamforming strategy based on the derivation of the expected signal-to-interference-plus-noise ratio (SINR). Then, according to users' feedback about their decisions, a successive user and beamforming selection algorithm is performed at the BSs. From simulation results, we show that, combined with proportional fair scheduling, the proposed scheme provides excellent throughput performance with very low computational complexity and the amount of inter-BS CSI exchange. Furthermore, we discuss an extension of the proposed scheme to limited feedback systems and observe that our algorithm also provides similar advantages over conventional schemes with quantized feedback. [ABSTRACT FROM PUBLISHER]

Source localization especially direction-of-arrival (DOA) estimation using sensor arrays is of considerable interest in both classical array signal processing and radar applications. Most radar systems are designed under the line-of-sight (LOS) assumption with multipath echos treated as undesired clutter noise. Strong multipath, therefore, has a negative impact on the resolution of the radar systems and their ability in accurately localizing the target. Rather than treating multipath as a detrimental effect, the paper introduces time reversal (TR) to exploit spatial/multipath diversity in improving the capability of the existing localization algorithms. In particular, we design TR based range and DOA estimators that adaptively adjust the probing radar waveforms to the multipath characteristics of the environment. The benefits of the spatial/multipath diversity in the proposed DOA and range estimators are quantified by deriving the respective Cramér–Rao bounds (CRB) and comparing them with the analytical expressions for their conventional counterparts. Numerical simulations also confirm the benefit of applying TR to source localization algorithms especially at low signal-to-noise ratios below -5 dB. [ABSTRACT FROM AUTHOR]

Base station cooperation improves the sum-rates that can be achieved in cellular systems. Conventional cooperation techniques require sharing large amounts of information over finite-capacity backhaul links and assume that base stations have full channel state information (CSI) of all the active users in the system. In this paper, a new limited feedback strategy is proposed for multicell beamforming where cooperation is restricted to sharing only the CSI of active users among base stations. The system setup considered is a linear array of cells based on the “soft hand-off model,” where each cell contains single-antenna users and multi-antenna base stations. Beamforming vectors are designed using a generalized eigenvector approach to maximize the sum-rate in a single-interferer scenario, at high signal to noise ratio. Users are assumed to feedback quantized CSI of the desired and interfering channels using a finite-bandwidth feedback link. An upper bound on the mean loss in sum rate due to random vector quantization is derived. A new feedback-bit allocation strategy, to partition the available bits between the desired and interfering channels, is developed to reduce the mean loss in sum-rate due to quantization for the soft hand-off model. The proposed feedback-bit partitioning algorithm is shown, using simulations, to yield sum-rates close to the those obtained using full CSI at base station. [ABSTRACT FROM AUTHOR]