A two-node binary chief executive officer (CEO) problem is investigated. Noise-corrupted versions of a binary sequence are forwarded by two nodes to a single destination node over orthogonal additive white Gaussian noise (AWGN) channels. We first reduce the binary CEO problem to a binary multiterminal source coding problem, of which an outer bound for the rate-distortion region is derived. The distortion function is then established by evaluating the relationship between the binary CEO and multiterminal source coding problems. A lower bound approximation on the Hamming distortion (HD) is obtained by minimizing a distortion function subject to constraints obtained based on the source-channel separation theorem. Encoding/decoding algorithms using concatenated convolutional codes and a joint decoding scheme are used to verify the lower bound on the HD. It is found that the theoretical lower bounds on the HD and the computer simulation-based bit error rate performance curves have the same tendencies. The differences in the threshold signal-to-noise ratio between the theoretical lower bounds and those obtained by simulations are around 1.5 dB in AWGN channel. The theoretical lower bound on the HD in block Rayleigh fading channel is also evaluated by performing Monte Carlo simulation.

Linear coordinated transmit-receive beamforming methods are proposed for spatial underlay direct device-to-device (D2D) communication in cellular networks where both user terminals (UT) and base stations (BS) employ multiple antenna elements. For a D2D terminal pair, direct communication is a beneficial alternative compared to the cellular mode, where the direct data is relayed via BS. The transmitter and receiver design is formulated as a weighted sum-rate (WSR) maximization problem subject to individual transmit power constraints at BSs and users, where the utility is the aggregate sum of end-to-end data rates carried via uplink, downlink, and D2D links. The direct D2D links are allowed to co-exist with the cellular connections. The original problem is reformulated as an equivalent log-MSE minimization problem allowing alternating optimization of the transmit and receive beamformers. The precoder optimization step is efficiently solved using successive convex approximation (SCA) of the non-convex objective and constraints. According to the results, the system performance can be significantly improved with efficient mode selection between the BS and D2D transmission as opposed to solely serving all the users via D2D links or BS. Also, in certain scenarios, it is beneficial to allow a multi-route connection between the UTs.

One of the promising candidates for mitigating the inter-cell interference in multi-cell networks is coordinated beamforming (CB), where cells are allowed to cooperate such that the transmission from each cell takes into account the interference it would cause to the users of other cells. In this work, we study the performance of a centralized algorithm which enables beam coordination in multi-cell multi-user multiple-input multiple-output (MIMO) network. The algorithm aims at maximizing the weighted sum rate (WSR) via weighted sum mean squared error (WSMSE) minimization, taking into account the estimation noise of channel state information (CSI). The performance is studied in a seven-cell network and the numerical results show that also with inaccurate CSI, CB outperforms traditional orthogonal access (OA) scheme where the same frequency resources are not reused between cells.

We propose a decentralized algorithm and corresponding low overhead signaling concepts of effective channel state information (CSI) for weighted sum rate (WSR) maximization via linear downlink transmit-receive beamforming in multi-cell multi-user MIMO systems operating in the time division duplex (TDD) mode. The proposed iterative processing consists of optimization steps that are run locally by base stations (BS), and facilitated by a combination of over-the-air uplink pilot signaling and scalar backhaul information exchange. In the uplink pilot signaling phase, each multi-antenna user terminal (UT) transmits a single precoded pilot beam. In case the UT was actively receiving, the uplink beam reveals its effective channel to all the coordinating BSs. On the other hand, if the UT was not receiving, the beam indicates its strongest effective vector channel to the serving BS. The processing strategy follows the changes of the time-varying channel and performs spatial user scheduling dynamically. According to the results, the strategy converges on the average in static channels, and in time-varying channels it effectively tracks the changes.

We propose decentralized algorithms and corresponding channel state information (CSI) signaling concepts for weighted sum rate (WSR) maximization via linear downlink transmit-receive processing in multi-cell multi-user MIMO systems operating in the time division duplex (TDD) mode. Decentralized processing relies on a combination of over-the-air pilot signaling and scalar information exchange between the base stations. Each base station (BS) computes the transmit precoders to serve its own user terminals locally. Similarly, the terminals compute their receive filters locally and signal their effective downlink channels to the BSs via precoded uplink sounding. As a result, the transmit strategies of the neighboring cells adapt to each other over time. WSR maximization results in the desirable property that spatial scheduling, or user and beam selection, is carried out implicitly. Thus, only a subset of the potential transmit beams are allocated with non-zero transmit powers.

A decentralized solution is proposed for the coordinated multi-cell multi-antenna minimum power beamformer design problem with single-antenna users. The optimal minimum power beamformers can be obtained locally at each base station (BS) relying on limited backhaul information exchange between BSs. The original centralized problem is reformulated such that the BSs are coupled by real-valued inter-cell interference terms. The coupling is handled by taking local copies of the interference terms at each BS and enforcing consistency between them. The consistency constraints are then decoupled by a standard dual decomposition approach leading to a distributed algorithm. The proposed method is able to guarantee feasible solutions even if the interference information is outdated or incomplete. In addition, the proposed approach allows for a number of special cases, where the backhaul information exchange is reduced at the cost of somewhat sub-optimal performance. The performance of the proposed coordinated multi-cell transmission is compared with the coherent multi-cell beamforming and with inter-cell interference nulling in different scenarios with varying interference. A near-optimal performance can be achieved even with significantly reduced backhaul information exchange and with relatively high velocities and/or low backhaul signaling rates.

A distributed solution is proposed for the coordinated multi-cell multi-antenna minimum power beamformer design problem with single-antenna users. The minimum power beamformers are obtained locally at each base station (BS) relying on limited backhaul information exchange between adjacent BSs. The original centralised problem is reformulated such that the BSs are coupled by real-valued inter-cell interference terms. The coupled interference terms are handled by taking local copies of the terms at each BS and enforcing consistency between them. The consistency constraints are then decoupled by a standard dual decomposition approach leading to a distributed algorithm. The proposed method is able to guarantee feasible solutions even if the interference information is outdated or incomplete, at the possible cost of increased sum power. In addition, the proposed approach allows for a number of special cases, where the backhaul information exchange is reduced at the cost of somewhat sub-optimal performance. The performance of the proposed coordinated multi-cell transmission is compared with the coherent multi-cell beamforming, as well as, with inter-cell interference nulling in different scenarios with varying interference. The numerical examples demonstrate that a near-optimal performance can be achieved even with significantly reduced backhaul information exchange.

A distributed implementation of coordinated multi-cell beamforming with single-antenna users in a time-correlated fading scenario is considered. The minimum power beamformers are obtained locally at each base station (BS) relying on limited backhaul information exchange between adjacent BSs. The original centralised problem is reformulated such that the BSs are coupled by real-valued inter-cell interference terms. The problem is then decoupled by a standard dual decomposition approach leading to a distributed algorithm. The method is able to guarantee feasible solutions even if the interference information is incomplete or outdated. Occasional high peaks in the transmitted power due to outdated interference terms are alleviated by switching to interference nulling mode when necessary. The performance of the proposed coordinated multi-cell transmission is compared with the coherent multi-cell beamforming, as well as, with interference nulling in different time-correlated fading scenarios with varying interference. The numerical examples demonstrate that a near-optimal performance can be achieved even with significantly reduced backhaul information exchange and with relatively high velocities and/or low signalling rates.

Coordinated linear transmitter-receiver processing by block diagonalization (BD) with beam selection is a straightforward method to utilize all degrees of freedom available in multiuser multiple-input multiple-output (MIMO) networks in order to increase system capacity. By applying channel state information (CSI) in the transmitter, the BD criterion offers zero- forcing between the downlink data streams of different users. This paper proposes practical uplink MIMO schemes for time division duplex (TDD) systems to co-exist with downlink TX-RX zero-forcing so that the locally available CSI of the BD channel is used by the terminals in the uplink transmission. It is shown that the preceded pilot symbols are sufficient in both uplink and downlink to satisfy the needs of both transmission and reception. The achievable rate of the system is evaluated in conjunction with linear receivers in a time-varying fading channel and with channel estimation. According to the results the proposed uplink transmission strategy provides increased rates compared to user selection as well as non-precoded transmission, without being sensitive to CSI uncertainty.

Coordinated multi-cell processing facilitates multiuser preceding techniques across distributed base station (BS) antenna heads. Hence, it can efficiently exploit the available spatial degrees of freedom in a multi-user multiple-input multiple-output (MIMO) channel. A generalised method for joint design of linear transceivers with coordinated multi-cell processing subject to per-BS/antenna power constraints is proposed. The system optimisation objective is to balance the weighted SINR across all the transmitted data streams. The method can accommodate a variety of scenarios from coherent multi-cell beamforming across a large virtual MIMO channel to single-cell beamforming with inter- cell interference coordination and beam allocation. The performance of different coherent/non-coherent and coordinated/non-coordinated multi-cell transmission methods with optimal and heuristic beam allocation algorithms is numerically compared in different scenarios with varying inter-cell interference. The coherent multi-cell beamforming greatly outperforms the noncoherent cases, especially at the cell edge and with a full spatial load. However, the coordinated single-cell transmission with interference avoidance and dynamic beam allocation performs considerably well with a partial spatial loading.

Block diagonalization (BD) is a downlink multiuser multiple-input multiple-output (MIMO) strategy that utilizes transmitter channel state information (CSI). This paper proposes a practical uplink MIMO scheme for time division duplex (TDD) systems to co-exist with BD, so that the CSI of the BD channels is used also in the uplink transmission. It is shown that the precoded pilot symbols are sufficient in both uplink and downlink to satisfy the needs of both transmission and reception. The capacity of the system is analyzed in conjunction with linear receivers in a time-varying fading channel. According to the results the proposed uplink strategy provides capacity gain over non-precoded transmission, without being sensitive to Doppler.

In order to perform coherent demodulation in fading channel conditions, channel phase and amplitude estimation is necessary. In a WCDMA downlink, the common pilot code channel is used for channel estimation in order to facilitate multipath diversity combining. The quality of the channel estimates may be improved by averaging or filtering over several pilot symbols. However, the optimal form and bandwidth of the estimation filter depend on the channel fading statistics and signal-to-interference ratio. In this paper, we investigate pilot aided channel estimation through adaptive filtering. Thus, near optimum channel estimates are obtained with different fading channel speeds and frequency offsets.

Adaptive interference cancellation schemes can offer a low-complexity means for alleviating the near-far problem pertinent in cellular CDMA systems. Bootstrap decorrelators have been proposed for simultaneous separation of all mutually interfering signals. Here, without any loss in performance, the bootstrap is simplified into a new adaptive scheme suitable for the downlink situation, i.e. for the detection of one desired user's signal.

Turbo codes are parallel concatenated codes whose performance in the additive white Gaussian noise (AWGN) channel has been shown to be near the theoretical limit. In this paper, we describe a low-rate superorthogonal turbo code that combines the principles of low-rate convolutional coding and that of parallel concatenation. Due to the bandwidth expansion, this code outperforms the ordinary turbo code both in AWGN and especially in fading channels. Thus, superorthogonal turbo codes are suited mainly for spread-spectrum applications. For the purposes of iterative decoding, we concisely describe the connection between the optimal maximum a posteriori symbol estimation and suboptimal soft-output decoding based on sequence estimation. The suboptimal decoder produces outputs that can directly be used as additive metrics at successive decoding iterations, without the need for estimating channel noise variance. Simulation results in AWGN and flat Rayleigh fading channels are also presented, along with analytical upper bounds of bit- and frame-error probabilities.

Turbo-codes are parallel concatenated convolutional codes (PCCC) whose performance in an AWGN channel has been shown to be near the Shannon limit. We describe a low rate superorthogonal turbo-code that outperforms the ordinary turbo-code at the expense of bandwidth expansion both in AWGN and especially in fading channels. Thus superorthogonal turbo-codes are suited mainly for e.g. CDMA applications. We concisely describe the soft output Viterbi (1995) algorithm using a priori inputs (APRI-SOVA) with connection to optimal maximum a posteriori (MAP) symbol estimation. Simulation results in AWGN and fading channels are also presented.