Fast algorithm for data exchange in reconfigurable tree structures

This paper presents a fast algorithm for data exchange in a network of processors organized as a reconfigurable tree structure. For a given data exchange table, the algorithm generates a sequence of tree configurations in which the data exchanges are to be executed. A significant feature of the algorithm is that each exchange is executed in a tree configuration in which the source and destination nodes are adjacent to each other. It has been proved in a theorem that for every pair of nodes in the reconfigurable tree structure, there always exists two and only two configurations in which these two nodes are adjacent to each other. The algorithm utilizes this fact and determines the solution so as to optimize both the number of configurations required and the time to perform the data exchanges. Analysis of the algorithm shows that it has linear time complexity, and provides a large reduction in run-time as compared to a previously proposed algorithm. This is well-confirmed from the experimental results obtained by executing a large number of randomly-generated data exchange tables. Another significant feature of the algorithm is that the bit-size of the routing information code is always two bits, irrespective of the number of nodes in the tree. This not only increases the speed of the algorithm but also results in simpler hardware inside each node.

Blind separation of multiple co-channel BPSK signals arriving at an antenna array

In this letter, we propose a method for blind separation of d co-channel BPSK signals arriving at an antenna array. Our method involves two steps. In the first step, the received data vectors at the output of the array is grouped into 2d clusters. In the second step, we assign the 2d d-tuples with ±1 elements to these clusters in a consistent fashion. From the knowledge of the cluster to which a data vector belongs, we estimate the bits transmitted at that instant. Computer simulations are used to study the performance of our method

Nonresonant edge slot antenna for phased array applications: Theory and experiment

The design and development of nonresonant edge slot antenna for phased array applications has been presented. The radiating element is a slot cut on the narrow wall of rectangular waveguide (edge slot). The admittance characteristics of the edge slot have been rigorously studied using a novel hybrid method. Nonresonant arrays have been fabricated using the present slot characterization data and the earlier published data. The experimentally measured electrical characteristics of the antenna are presented which clearly brings out the accuracy of the present method.

On Training and Training Voids for Receive Antenna Subset Selection in Time-Varying Channels

Antenna selection (AS) provides most of the benefits of multiple-antenna systems at drastically reduced hardware costs. In receive AS, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. The "best" subset to be used for data reception is determined by means of channel estimates acquired using training sequences. Due to the nature of AS, the channel estimates at different antennas are obtained from different transmissions of the pilot sequence, and are, thus, outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N, we highlight a new issue of "training voids", in which the last pilot transmission is not fully exploited by the receiver. We present a "void-filling" method for fully exploiting these voids, which essentially provides more accurate training for some antennas, and derive the optimal subset selection rule for any void-filling method. We also derive new closed-form equations for the performance of receive AS with optimal subset selection.

A double U-slot patch antenna with dual wideband characteristics

Microstrip patch antennas are strong candidates for use in many wireless communications applications. This paper proposes the use of a patch antenna with two U-shaped slots to achieve dual band operation. A thick substrate helps broaden the individual bandwidths. The antenna is designed based on extensive IE3D simulation studies. A prototype antenna is fabricated and experimentally verified for the required performance.

Elliptic slot antenna for broadband wireless communications

This paper presents the design of a broadband antenna suitable for wireless communications operating over the frequency range of 3.1-10.6 GHz. Parametric studies on the effect of stub and elliptic slot have been carried out to arrive at optimum dimensions to achieve enhanced bandwidth of the proposed antenna. An experimental antenna has been designed and tested to validate the proposed design. Measured return loss characteristics have been compared against the simulation results. Simulated radiation patterns at 3.1 GHz, 6.85 GHz and 10.6 GHz have also been presented in this paper.

Training and Voids in Receive Antenna Subset Selection in Time-Varying Channels

Receive antenna selection (AS) provides many benefits of multiple-antenna systems at drastically reduced hardware costs. In it, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. Due to the nature of AS, the channel estimates at different antennas, which are required to determine the best subset for data reception, are obtained from different transmissions of the pilot sequence. Consequently, they are outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is necessary and optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N , we highlight a new issue of ``training voids'', in which the last pilot transmission is not fully exploited by the receiver. We then present new ``void-filling'' methods that exploit these voids and greatly improve the performance of AS. The optimal subset selection rules with void-filling, in which different antennas turn out to have different numbers of estimates, are also explicitly characterized. Closed-form equations for the symbol error probability with and without void-filling are also developed.

Antenna Selection for Next Generation IEEE 802.16 Mobile Stations

The IEEE 802.16/WiMAX standard has fully embraced multi-antenna technology and can, thus, deliver robust and high transmission rates and higher system capacity. Nevertheless,due to its inherent form-factor constraints and cost concerns, a WiMAX mobile station (MS) should preferably contain fewer radio frequency (RF) chains than antenna elements.This is because RF chains are often substantially more expensive than antenna elements. Thus, antenna selection, wherein a subset of antennas is dynamically selected to connect to the limited RF chains for transceiving, is a highly appealing performance enhancement technique for multi-antenna WiMAX terminals.In this paper, a novel antenna selection protocol tailored for next-generation IEEE 802.16 mobile stations is proposed. As demonstrated by the extensive OPNET simulations, the proposed protocol delivers a significant performance improvement over conventional 802.16 terminals that lack the antenna selection capability. Moreover, the new protocol leverages the existing signaling methods defined in 802.16, thereby incurring a negligible signaling overhead and requiring only diminutive modifications of the standard. To the best of our knowledge, this paper represents the first effort to support antenna selection capability in IEEE 802.16 mobile stations.

Dynamically Reconfigurable Regular Expression Matching Architecture

Regular Expressions are generic representations for a string or a collection of strings. This paper focuses on implementation of a regular expression matching architecture on reconfigurable fabric like FPGA. We present a Nondeterministic Finite Automata based implementation with extended regular expression syntax set compared to previous approaches. We also describe a dynamically reconfigurable generic block that implements the supported regular expression syntax. This enables formation of the regular expression hardware by a simple cascade of generic blocks as well as a possibility for reconfiguring the generic blocks to change the regular expression being matched. Further,we have developed an HDL code generator to obtain the VHDL description of the hardware for any regular expression set. Our optimized regular expression engine achieves a throughput of 2.45 Gbps. Our dynamically reconfigurable regular expression engine achieves a throughput of 0.8 Gbps using 12 FPGA slices per generic block on Xilinx Virtex2Pro FPGA.

Integer Sequence window based Reconfigurable FIR filters

Conventional hardware implementation techniques for FIR filters require the computation of filter coefficients in software and have them stored in memory. This approach is static in the sense that any further fine tuning of the filter requires computation of new coefficients in software. In this paper, we propose an alternate technique for implementing FIR filters in hardware. We store a considerably large number of impulse response coefficients of the ideal filter (having box type frequency response) in memory. We then do the windowing process, on these coefficients, in hardware using integer sequences as window functions. The integer sequences are also generated in hardware. This approach offers the flexibility in fine tuning the filter, like varying the transition bandwidth around a particular cutoff frequency.

Antenna Selection Training in MIMO-OFDM/OFDMA Cellular Systems

Antenna selection allows multiple-antenna systems to achieve most of their promised diversity gain, while keeping the number of RF chains and, thus, cost/complexity low. In this paper we investigate antenna selection for fourth-generation OFDMA- based cellular communications systems, in particular, 3GPP LTE (long-term evolution) systems. We propose a training method for antenna selection that is especially suitable for OFDMA. By means of simulation, we evaluate the SNR-gain that can be achieved with our design. We find that the performance depends on the bandwidth assigned to each user, the scheduling method (round-robin or frequency-domain scheduling), and the Doppler spread. Furthermore, the signal-to-noise ratio of the training sequence plays a critical role. Typical SNR gains are around 2 dB, with larger values obtainable in certain circumstances.