Semi-blind Channel Estimation and Data Detection for Multi-cell Massive MIMO Systems on Time-Varying Channels

We study the problem of semi-blind channel estimation and symbol detection in the uplink of multi-cell massive MIMO systems with spatially correlated time-varying channels. An algorithm based on expectation propagation (EP) is developed to iteratively approximate the joint a posteriori distribution of the unknown channel matrix and the transmitted data symbols with a distribution from an exponential family. This distribution is then used for direct estimation of the channel matrix and detection of data symbols. A modified version of the popular Kalman filtering algorithm referred to as KF-M emerges from our EP derivation and it is used to initialize the EP-based algorithm. Performance of the Kalman smoothing algorithm followed by KF-M is also examined. Simulation results demonstrate that channel estimation error and the symbol error rate (SER) of the semi-blind KF-M, KS-M, and EP-based algorithms improve with the increase in the number of base station antennas and the length of the transmitted frame. It is shown that the EP-based algorithm significantly outperforms KF-M and KS-M algorithms in channel estimation and symbol detection. Finally, our results show that when applied to time-varying channels, these algorithms outperform the algorithms that are developed for block-fading channel models.Comment: 28 pages, 13 figures, Submitted to IEEE Trans. on Vehicular Technolog

A Hop-by-Hop Relay Selection Strategy in Multi-Hop Cognitive Relay Networks

In this paper, a hop-by-hop relay selection strategy for multi-hop underlay cognitive relay networks (CRNs) is proposed. In each stage, relays that successfully decode the message from previous hop form a decoding set. Taking both maximum transmit power and maximum interference constraints into consideration, the relay in the decoding set which has the largest number of channels with an acceptable signal-to-noise ratio (SNR) level to the relays in the next stage is selected for retransmission. Therefore, relay selection in each stage only relies on channel state information (CSI) of the channels in that stage and does not require the CSI of any other stage. We analyze the performance of the proposed strategy in terms of endto-end outage probability and throughput, and show that the results match those obtained from simulation closely. Moreover, we derive the asymptotic end-to-end outage probability of the proposed strategy when there is no upper bound on transmitters’ power. We compare this strategy to other hop-by-hop strategies that have appeared recently in the literature and show that this strategy has the best performance in terms of outage probability and throughput. Finally it is shown that the outage probability and throughput of the proposed strategy are very close to that of exhaustive strategy which provides a lower bound for outage probability and an upper bound for throughput of all path selection strategies

Bandwidth and buffer dimensioning for guaranteed quality of service in wireless ATM networks

Extending ATM services to the wireless environment is intended to provide quality of service guarantees to multimedia applications. However, provisioning of QoS over the wireless link is made difficult by the fact that the burstiness of the channel and the retransmission mechanism of the data link layer protocol result in a randomly varying transmission rate for the ATM connection. In this paper the randomly varying connection rate is modeled by a generalized Gilbert/Elliot channel model. A queueing analysis is performed for this system and the cell loss rate from the transmittetter\u27s buffer is evaluated in terms of the connection\u27s allocated bandwidth, the buffer size and the parameters of the FEC code used in the ARQ system. Numerical results are presented for the cell loss rate as a function of the system parameters. These can be used for bandwidth allocation, buffer dimensioning and optimal code rate selection in order to guarantee the cell loss performance of the connection

Bandwidth and Buffer Dimensioning for Guaranteed Quality of Service in Wireless ATM Networks

Extending ATM services to the wireless environment is intended to provide quality of service guarantees to multimedia applications. However, provisioning of QoS over the wireless link is made difficult by the fact that the burstiness of the channel and the retransmission mechanism of the data link layer protocol result in a randomly varying transmission rate for the ATM connection. In this paper the randomly varying connection rate is modeled by a generalized Gilbert/Elliot channel model. A queueing analysis is performed for this system and the cell loss rate from the transmitter's buffer is evaluated in terms of the connection's allocated bandwidth, the buffer size and the parameters of the FEC code used in the ARQ system. Numerical results are presented for the cell loss rate as a function of the system parameters. These can be used for bandwidth allocation, buffer dimensioning and optimal code rate selection in order to guarantee the cell loss performance of the connection

A unitary MUSIC-like algorithm for coherent sources

This paper proposes a method for direction of arrival (DOA) estimation which can be applied in case of both non-coherent and coherent sources. In comparison to the well-known subspace algorithms such as MUSIC, the proposed method has several advantages. First, in contrast to MUSIC, no forward/backward spatial smoothing for the covariance matrix is needed in the case of coherent sources. Second, the proposed method is more suitable for realtime implementation since it only requires one or a few snapshots in order to provide an accurate DOA estimation, whereas MUSIC requires a large number of snapshots. Third, the proposed method exploits the eigenvalue decomposition (EVD) of a real-valued covariance matrix thereby reducing the computational cost by at least a factor of four. Simulation results show that the proposed method can estimate the DOAs of the incident sources with high accuracy even when the sources are coherent. © 2007 IEEE

Call admission control for CDMA cellular networks supporting multimedia services

A new call admission control algorithm is presented and analyzed for CDMA networks supporting multimedia services. Our algorithm uses a criterion based on the average SIR as well as the effective bandwidth of the connections. Handoff requests receive higher priority through resource reservation. The proposed algorithm is easy to implement as it only needs to examine the number of current connections in the cell in order to admit or reject a new connection request. The performance of the algorithm is evaluated in terms of blocking probabilities of new and handoff calls, outage probabilities and system throughput. Our results show that our algorithm achieves performance similar to those published in the literature with considerably less implementation complexity. © 2006 IEEE

Diversity techniques for spectrum sensing in fading environments

A key feature of a cognitive radio (CR) is a reliable spectrum sensing technique which enables the CR to detect the so-called white spaces in the frequency band. This allows opportunistic access of the unlicensed (secondary) users to these white spaces without causing undue interference to licensed (primary) users. In many scenarios the CR may operate in a multipath fading environment where spectrum sensing must cope with the fading effects of the unknown primary signal. In this paper we first study the effects of multipath fading of the performance of the autocorrelation-based spectrum sensing algorithm in [1]. The results show that Rayleigh fading causes significant degradation in the detection and false alarm. This motivates us to investigate three diversity combining techniques, namely equal gain combining, selective combining, and equal gain correlation combining. For Rayleigh fading channels we evaluate the performance of these three techniques through simulation. The results show that for detection probabilities of interest (e.g., \u3e .9), a system with a four-branch diversity achieves an SNR gain of more than 5 dB over the no-diversity system that uses the same number of received signal samples. ©2008 IEEE

EM-Based Localization of Noncooperative Multicarrier Communication Sources with Noncoherent Subarrays

Multicarrier communication signals possess distinct characteristics different from narrowband signals often targeted by localization algorithms. Each source occupies a unique set of subcarriers and is practically absent from other subcarriers. Moreover, subcarrier allocation for a source may change over time. In noncooperative geolocation applications, knowledge of the set of subcarriers occupied by a source may not be available. This paper proposes iterative localization algorithms which jointly estimate the locations of the sources in both the spatial and spectral domains. It is assumed that the transmitted signals are intercepted by spatially dispersed subarrays which are asynchronous. This eliminates the need for accurate clock synchronization across the geographically distributed subarrays. The proposed method is based on the expectation-maximization (EM) algorithm, and the subcarrier occupancy detection is achieved via the likelihood ratio test within each the EM iteration. The performance of the algorithm is evaluated through simulation for a multi-source localization problem. It is shown that for signal-to-noise ratios of interest, the proposed method achieves a performance close to the algorithm, which is aware of all the subcarrier allocations

Nonparametric density estimation, hypotheses testing, and sensor classification in centralized detection

In distributed sensing, the statistical model of the data collected by the sensor elements is often unavailable. In addition, these statistics may vary among the sensors and over time, for instance due to: 1) hardware variations; 2) the sensors\u27 geographical locations; 3) different noise statistics; 4) diverse channel conditions between the sensor elements and the fusion center (FC); and 5) the presence of misbehaving sensors sending false data to the FC. In this paper, we consider the problem of centralized binary hypothesis testing in a wireless sensor network consisting of multiple classes of sensors, where the sensors are classified according to the probability density function (PDF) of their received data (at the FC) under each hypothesis. The sensor nodes transmit their observed data to the FC, which must classify the nodes and detect the state of nature. To optimally fuse the data, the FC must also estimate the PDFs of the sensors\u27 observations. We develop a method based on the expectation maximization (EM) algorithm to estimate the PDFs for each sensor class, to classify the sensors, and to detect the underlying hypotheses. The estimation of PDFs is nonparametric in that no prior model is assumed. Simulation results using fewer than three iterations of the EM algorithm demonstrate the efficacy of the proposed method. © 2014 IEEE