Abstract-Space-time block codes (STBCs) that are single-symbol decodable (SSD) in a co-located multiple antenna setting need not be SSD in a distributed cooperative communication setting. A relay network with N relays and a single source-destination pair is called a partially-coherent relay channel (PCRC) if the destination has perfect channel state information (CSI) of all the channels and the relays have only the phase information of the sourceto-relay channels. In this paper, first, a new set of necessary and sufficient conditions for a STBC to be SSD for co-located multiple antenna communication is obtained. Then, this is extended to a set of necessary and sufficient conditions for a distributed STBC (DSTBC) to be SSD for a PCRC, by identifying the additional conditions. Using this, several SSD DSTBCs for PCRC are identified among the known classes of STBCs. It is proved that even if a SSD STBC for a co-located MIMO channel does not satisfy the additional conditions for the code to be SSD for a PCRC, single-symbol decoding of it in a PCRC gives full-diversity and only coding gain is lost.

The Tucker decomposition expresses a given tensor as the product of a small core tensor and a set of factor matrices. Apart from providing data compression, the construction is useful in performing analysis such as principal component analysis (PCA) and finds applications in diverse domains such as signal processing, computer vision and text analytics. Our objective is to develop an efficient distributed implementation for the case of dense tensors. The implementation is based on the HOOI (Higher Order Orthogonal Iterator) procedure, wherein the tensor-times-matrix product forms the core routine. Prior work have proposed heuristics for reducing the computational load and communication volume incurred by the routine. We study the two metrics in a formal and systematic manner, and design strategies that are optimal under the two fundamental metrics. Our experimental evaluation on a large benchmark of tensors shows that the optimal strategies provide significant reduction in load and volume compared to prior heuristics, and provide up to 7x speed-up in the overall running time.

Abstract-In uplink orthogonal frequency division multiple access (OFDMA) systems, multiuser interference (MUI) occurs due to different carrier frequency offsets (CFO) of different users at the receiver. In this paper, we present a minimum mean square error (MMSE) based approach to MUI cancellation in uplink OFDMA. We derive a recursion to approach the MMSE solution. We present a structure-wise and performance-wise comparison of this recursive MMSE solution with a linear PIC receiver as well as other detectors recently proposed in the literature. We show that the proposed recursive MMSE solution encompasses several known detectors in the literature as special cases.

Abstract-In uplink orthogonal frequency division multiple access (OFDMA) systems, multiuser interference (MUI) occurs due to different carrier frequency offsets (CFO) of different users at the receiver. In this paper, we present a multistage linear parallel interference cancellation (LPIC) approach to mitigate the effect of this MUI in uplink OFDMA. The proposed scheme first performs CFO compensation (in time-domain) followed by K DFT operations (where K is the number of users) and multistage LPIC on these DFT outputs. We scale the MUI estimates by weights before cancellation and optimize these weights by maximizing the average signal-to-interference ratio (SIR) at the output of the different stages of the LPIC. We derive closed-form expressions for these optimum weights. The proposed LPIC scheme is shown to effectively cancel the MUI caused by the other user CFOs in uplink OFDMA. While our proposed approach performs CFO compensation in time-domain, an alternate approach proposed recently by Huang and Letaief performs CFO compensation and interference cancellation in frequency-domain. We show that our approach performs better than the Huang & Letaief's approach when the magnitude of the CFO differences (between desired user CFO and other user CFOs) are small, whereas their approach performs better when the magnitude of the individual CFOs (of other users) are small. Since the CFO values can be arbitrary at the receiver, in order to make the receiver robust under various CFO conditions, we propose simple metrics based on CFO knowledge, which the receiver can compute and use to choose between the time-domain (ours) and the frequency-domain (Huang & Letaief's) cancellers so that better performance among the two approaches is achieved under various CFO conditions. Index Terms-Carrier frequency offset, circular convolution, linear parallel interference cancellation, optimum weights, signalto-interference ratio, uplink OFDMA.

Synchronization issues pose a big challenge in cooperative communications. The benefits of cooperative diversity could be easily undone by improper synchronization. The problem arises because it would be difficult, from a complexity perspective, for multiple transmitting nodes to synchronize to a single receiver. For OFDM based systems, loss of performance due to imperfect carrier synchronization is severe, since it results in inter-carrier interference (ICI). The use of space-time/spacefrequency codes from orthogonal designs are attractive for cooperative encoding. But orthogonal designs suffer from intersymbol interference (ISI) due to the violation of quasi-static assumption, which can arise due to frequency-or time-selectivity of the channel. In this paper, we are concerned with combating the effects of i) ICI induced by carrier frequency offsets (CFO), and ii) ISI induced by frequency selectivity of the channel, in a cooperative communication scheme using space-frequency block coded (SFBC) OFDM. Specifically, we present an iterative interference cancellation (IC) algorithm to combat the ISI and ICI effects. The proposed algorithm could be applied to any orthogonal or quasi-orthogonal designs in cooperative SFBC OFDM schemes.