We live in the world of heterogeneous computing. With specialised elements reaching all aspects of our computer systems and their prevalence only growing, we must act to rein in their inherent complexity. One area that has seen significantly less investment in terms of development is heterogeneous-ISA systems, specifically because of complexity. To date, heterogeneous-ISA processors have required significant software overheads, workarounds, and coordination layers, making the development of more advanced software hard, and motivating little further development of more advanced hardware. In this paper, we take a fused approach to heterogeneity, and introduce a new operating system (OS) design, the fused-kernel OS, which goes beyond the multiple-kernel OS design, exploiting cache-coherent shared memory among heterogeneous-ISA CPUs as a first principle -- introducing a set of new OS kernel mechanisms. We built a prototype fused-kernel OS, Stramash-Linux, to demonstrate the applicability of our design to monolithic OS kernels. We profile Stramash OS components on real hardware but tested them on an architectural simulator -- Stramash-QEMU, which we design and build. Our evaluation begins by validating the accuracy of our simulator, achieving an average of less than 4% errors. We then perform a direct comparison between our fused-kernel OS and state-of-the-art multiple-kernel OS designs. Results demonstrate speedups of up to 2.1× on NPB benchmarks. Further, we provide an in-depth analysis of the differences and trade-offs between fused-kernel and multiple-kernel OS designs.

To improve resource utilization and reduce costs many Cloud providers adopt virtual machines (VMs) overcommitment. While effective, this strategy may lead to adverse outcomes, significantly affecting a VM IO performance when one virtual CPU (vCPU) is preempted by another vCPU within the same runqueue of the VM scheduler -- i.e., same physical CPU (pCPU). Additionally, the responsiveness of a VM is reduced during the inactive time of the vCPU, and it necessitates an extra schedule timeslice to react to any IO event. While such problems have been studied in academia and industry, no previous solution has been deployed in production. This is because for example certain solutions require modifications of the guest VM, which is in contrast with industry requirements.

Lower THz frequency in the range 100–300 GHz is an attractive candidate for the 6G communication system thanks to the large available bandwidth. To conduct system design from early on, there is a need to have a channel model for this frequency range. This paper presents a comprehensive channel parameters set for the 3GPP channel model in the frequency range 100–300 GHz. The channel parameters have been extracted from the measurement and ray tracing simulation data available in the literature. Insights into the specific behavior of the parameters have been provided as well. Additionally, a link budget analysis is provided to show the impact of the channel parameters on the 6G system design. The results show that 10–100 Gbps rates are achievable in the indoor scenario with the available bandwidth in the lower THz frequency.

Conventional single-vector-based direct torque control (SVB-DTC) has been widely researched owing to its simple control structure, parameter robustness and fast response. However, the SVB-DTC often features large torque and flux ripple. To suppress the large ripple in torque and stator flux, recently, a duty-cycle-based DTC (DCB-DTC) scheme applying a zero vector and a nonzero vector to the drive during every control period has been presented. However, the torque and flux ripple fail to be reduced to a minimal value owing to the fixed vector combination of a zero and a nonzero vector. A generalized two-vector-based DTC (GTV-DTC) for permanent-magnet synchronous machine (PMSM) drives which relaxes the vector combination to two arbitrary voltage vectors is proposed. In contrast to the DCB-DTC, two nonzero vectors might be chosen in the proposed method. Then the torque ripple can be reduced by the broad possible vector combination. In addition, a simple analytical and graphical method is proposed to select two voltage vectors and to determine their optimal durations based on the principle of stator flux vector error minimization. The simulation results are provided to verify the outstanding performance of the proposed method that, compared to prior SVB-DTC and DCB-DTC, the proposed GTV-DTC achieves much better steady-state performance and similar transient-state performance without significantly increasing computational burden.

Energy-efficient orthogonal frequency division multiple access (OFDMA) aims to relieve the booming energy consumption in wireless communications networks and has recently received lots of attention. Meanwhile, two-way relay has been extensively studied and proves to be more spectral-efficient than direct transmission and one-way relay in many scenarios. In this paper, we study energy-efficient resource allocation for OFDMA-based two-way relay, maximizing the aggregated energy efficiency (EE) utility while provisioning proportional fairness in EE among different terminal pairs. The energy-efficient joint power and subchannel allocation and active subchannel selection problem is mixed-integer combinatorial and further demonstrates to be nonconvex. To approach the performance limit, we first find an upper-bound solution relying on continuous relaxation and the Lagrange dual method. To reduce the computational complexity, we separate power allocation and subchannel assignment. To this regard, we exploit the hidden concavity and the pseudoconcavity in the subproblems for any fixed subchannel assignment and propose an EE-oriented sequential subchannel assignment policy. Besides, we discover the sufficient condition for early termination of the sequential subchannel assignment without losing the EE optimality. Simulation results demonstrate that the proposed energy-efficient OFDMA-based two-way relay can achieve much larger EE utility while provisioning proportional fairness in EE among different terminal pairs compared to its spectral-efficient counterpart.

This paper investigates energy-efficient device-to-device (D2D) communications in cellular networks. We aim to maximize the overall energy-efficiency (EE) of D2D users and regular cellular users (RCUs) while considering the circuit power consumption and the quality-of-service (QoS) requirements for both types of users as well as power constraints. Three transmission modes, namely, dedicated mode, reusing mode, and cellular mode, are considered for D2D users to share spectrum with RCUs. Parametric Dinkelbach method and concave-convex procedure (CCCP) are adopted to transform the original optimization problems into more tractable forms through sequential convex approximations. Then, interior point method is exploited to obtain the optimal solution. Simulation results show that system EE can be improved significantly with the proposed mode switching algorithm compared with the single mode transmission. Besides, it is also shown that the reusing mode is more preferred in the EE based mode switching while it is the dedicated mode in the spectrum-efficiency (SE) based mode switching in most situations.

Energy-efficient design in orthogonal frequency division multiple access (OFDMA) is becoming increasingly important, considering the booming energy consumption in wireless networks and the extensive deployment of OFDMA-based wireless infrastructures. On the other hand, wireless power transfer brings another promising approach for saving energy and prolonging lifetime in wireless networks by letting users scavenge energy from the received radio-frequency (RF) signals all over the wireless environments, including the desired information beams and undesired interference beams. In this paper, we study the downlink and uplink energy efficiency (EE) tradeoff in time-division duplexing (TDD) OFDMA with one access point (AP) and multiple users, where the users are allowed to split the received signals for decoding information and harvesting energy in the downlink, respectively. The established optimization problem turns to be an integer-mixed nonconvex program. Through relaxation and transformation, we develop a near-optimal resource allocation strategy that approaches the Pareto optimal tradeoff performance. Numerical results show that there may exist a tradeoff between the downlink and uplink EE and the AP can help improve the uplink EE by operating the downlink at the suboptimal EE regime.

Cognitive radio (CR) and energy-efficient design have emerged as two promising techniques to achieve high spectrum efficiency (SE) and energy efficiency (EE), respectively. In this paper, we study energy-efficient opportunistic spectrum access strategies for an orthogonal frequency division multiplexing (OFDM)-based CR network with multiple secondary users (SUs). Both worst EE and average EE are considered and optimized for different emphases and application scenarios. Since the original optimization issues belong to nonconvex integer combinatorial fractional program and are essentially NP-hard for an optimal solution, we use continuous and convex relaxation to modify the problems for somewhat better mathematical tractability. For the relaxed worst-EE-based spectrum access problem, we first demonstrate the joint quasiconcavity of EE on subchannel and power allocation matrices and then develop a framework to find the optimal solution based on efficient root finding and convex optimization. We also develop a low-complexity alternative for suboptimal solution. The relaxed average-EE-based spectrum access problem is still NP-hard and may have many local optima. We first transform the problem into an equivalent form and introduce a general concave envelope based branch-and-bound (B&B) approach to find the global optimal solution. We then exploit the underlying properties of the energy-efficient transmission to speed up the convergence of the B&B approach. Besides, we develop a low-complexity heuristic approach to find a suboptimal solution. Simulation results show that the energy-efficient spectrum access strategies significantly boost EE compared with the conventional spectral-efficient spectrum access ones while the low-complexity suboptimal approaches can well balance the performance and complexity.

To support the heterogeneous demands for the network and mobile user equipment (UE), multiple radio access technologies (RATs), operating with different system configurations and resources, have evolved and now coexist. Recently, with data traffic exponentially increasing, there has been a significant expansion in wireless network infrastructure, raising a justifiable concern over the concomitant drastic increase in energy consumption. Thus, energy-efficient design in multi-RAT networks is becoming increasingly important. In this paper, we consider resource allocation that maximizes the energy efficiency (EE) for orthogonal frequency division multiple access (OFDMA) in multi-RAT networks. To this end, we present the optimal resource allocation problem for parallel transmission utilizing multiple RATs. Since the formulated problem is NP-hard, a modified problem is proposed, for which a near-optimal resource allocation algorithm is developed by exploiting the intrinsic quasiconcavity of the problem. To reduce the computational complexity, we develop a low-complexity suboptimal allocation strategy based on joint iterative subcarrier and waterfilling power allocation over multiple RATs. Simulation results show that the proposed algorithms can achieve a higher EE compared to a conventional spectral-efficiency-based approach and can obtain performance comparable with the optimal solution, but with much less complexity.

Cognitive radio (CR) and energy-efficient design have emerged as two promising technologies to achieve high spectrum efficiency (SE) and energy efficiency (EE), respectively. In this paper, we study energy-efficient opportunistic spectrum access strategies for multiple secondary users (SUs) in an orthogonal frequency division multiplexing (OFDM)-based CR network. The worst EE is considered and optimized to achieve the max-min fairness. Since the original optimization issue belongs to nonconvex integer combinatorial fractional program and are essentially NP-hard for optimal solution, we use continuous and convex relaxation to modify the problem for somewhat better mathematical tractability. For the modified problem, we first develop a framework to find the optimal solution based on efficient root finding and convex optimization. We also develop a low-complexity alternative for suboptimal solution to further reduce complexity. Simulation results show that the energy-efficient spectrum access strategies significantly boost EE compared with the conventional spectral-efficient spectrum access ones. And the low-complexity suboptimal approaches can well balance the performance and complexity.

The tremendous popularity of smart phones and electronic tablets has spurred the explosive growth of high-rate multimedia services and promptly boomed energy consumption in wireless networks. Therefore, energy-efficient design in wireless networks is very important and is attracting more and more attention, just like the conventional spectral-efficient design. In this paper, we study energy-efficient design in downlink orthogonal frequency division multiple access (OFDMA) networks with effective capacity-based delay provisioning for delay-sensitive traffic. By integrating information theory with the concept of effective capacity, we formulate an energy efficiency (EE) optimization problem with statistical delay provisioning, which is a complicated nonconvex combinatorial fractional programming problem. To solve the problem, we first relax it with an upper bound on the original one and then prove and exploit the quasiconcave property of the EE-versus-transmit power curve, which facilitates the optimal algorithm development. Then, we demonstrate that the resultant solution is quite close to the true optimal value when the number of subcarriers is larger than that of the users. We also analyze the tradeoff between EE and delay, the relationship between spectral-efficient and energy-efficient designs, and the impact of system parameters, including circuit power and delay exponents, on the overall performance. Numerical results show that the proposed energy-efficient design scheme greatly improves EE while maintaining the delay requirement.

The ubiquitous applications of high-data-rate realtime wireless services have promptly boomed energy consumption in wireless networks. Therefore, energy-efficient design in wireless networks is very important and is attracting more and more research attention. In this paper, we study the quality-of-service (QoS) driven energy-efficient design in the downlink orthogonal frequency division multiple access (OFDMA) network. By integrating information theory with the concept of effective capacity, we formulate an energy efficiency (EE) optimization problem with statistical QoS provisioning. To solve the problem, we first modify it with a tight upper bound on the original EE and solve the modified problem. Then, we demonstrate that the resultant solution is quite close to the true optimal value when the number of subcarriers is large than that of the users. We also find out the tradeoff relation between EE and delay. Numerical results show that the proposed energy-efficient design scheme greatly improves EE whiling maintaining QoS requirements.

Widespread application of multimedia wireless services and requirement of ubiquitous access have triggered rapidly booming energy consumption at both transmitter and the receiver sides. Hence, energy-efficient design in wireless networks is very important and is becoming an inevitable trend. In this paper, we take decoding power into consideration when studying joint transmitter and receiver design for achieving high energy efficiency (EE). Based on a new function between transmit power and data rate that is derived by minimizing a lower bound on the overall transmit and receiver power, we investigate when and how should the decoding power be considered for optimizing EE. We find that the decoding power cannot be ignored for short-range wireless communications with a large bandwidth where the transmit power is usually low and give an analytical expression for quantifying the impact of decoding power on EE.

The fixed-complexity sphere decoder (FSD) has been proposed to attain the near-optimal performance achieving the same diversity order as the maximum-likelihood decoder (MLD) recently. However, it suffers great redundant computations resulting in high power consumption. In this paper, we conduct an improved algorithm for the original FSD by using early termination (ET). This algorithm (abbreviated as ET-FSD) preserves the advantages of sphere decoder (SD) such as branch pruning and an adaptively updated pruning threshold. We compare the ET-FSD with the original FSD and a lately developed statistical threshold-based FSD (ST-FSD). Simulation results demonstrate that the ET-FSD attains the same performance with a much lower cost than the FSD, and is much more efficient than the ST-FSD in practice. In addition, the statistical threshold-based method can also be used for the ET-FSD (i.e., ST-ET-FSD) to further reduce the complexity.

The explosively increasing demand of high-data-rate multimedia wireless services and ubiquitous access has triggered rapidly booming energy consumption at the wireless network operator side. Therefore, energy-efficient design is becoming a mainstream for future wireless networks. In this paper, we study energy-efficient resource allocation in downlink OFDMA networks with partial channel state information at the transmitter (CSIT). To reduce the channel state information (CSI) feedback overhead while maintaining relatively high achievable energy efficiency (EE), we propose a novel CSI feedback scheme, which leads to higher EE with lower feedback overhead compared with the conventional selective feedback (SF) and bit-map based feedback (BF) schemes. Simulation results show that the energy-efficient design greatly improves EE compared with that of the conventional spectral-efficient design and our CSI feedback scheme outperforms the conventional CSI feedback schemes in EE and spectral efficiency (SE) with almost the same feedback overhead.

The widespread application of multimedia wireless services and requirements of ubiquitous access have triggered rapidly booming energy consumption at both the base station side and the user equipment (UE) side. Hence, energy-efficient design in wireless networks is very important and is becoming an inevitable trend. In this paper, we study the energy-efficient resource allocation in both downlink and uplink cellular networks with orthogonal frequency division multiple access (OFDMA). For the downlink transmission, the generalized energy efficiency (EE) is maximized while for the uplink case the minimum individual EE is maximized, both under certain prescribed per-UE quality-of-service (QoS) requirements. For both transmission scenarios, we first provide the optimal solution and then develop a suboptimal but low-complexity approach by exploring the inherent structure and property of the energy-efficient design. For the downlink case, by modifying the original problem, we also find a computationally efficient and numerically tractable upper bound on the EE, which indicates the performance limit and is demonstrated to be quite tight if the number of subcarriers is larger than that of UEs and motivates us to find a near-optimal approach relying on the quasiconcave relation between the modified EE and transmit power. Simulation results show that the energy-efficient design greatly improves EE compared with the conventional spectral-efficient design and the low-complexity suboptimal approaches can achieve a promising tradeoff between performance and complexity.

The widespread application of multimedia wireless services and requirement of ubiquitous access have triggered rapidly booming energy consumption at both the base station side. Hence, energy-efficient design in wireless networks is very important and is becoming an inevitable trend. In this paper, we study energy-efficient resource allocation in downlink cellular OFDMA networks. For the downlink transmission, the weighted energy efficiency (EE) is maximized under certain prescribed per-user quality- of-service (QoS) requirements. We first obtain the optimal solution then propose a suboptimal approach by exploring the inherent structure and property of the energy-efficient design to reduce complexity. Simulation results show that the energy-efficient design greatly improves EE compared with that of the conventional spectral-efficient design and our low- complexity suboptimal approaches can achieve promising tradeoff between performance and complexity.

Conventional design of wireless networks mainly focuses on system capacity and spectral efficiency (SE). As green radio (GR) becomes an inevitable trend, energy-efficient design in wireless networks is becoming more and more important. In this paper, the fundamental tradeoff relation between energy efficiency (EE) and SE in downlink orthogonal frequency division multiple access (OFDMA) networks is addressed. We obtain a tight upper bound and lower bound on the optimal EE-SE tradeoff relation for general scenarios based on Lagrange dual decomposition, which accurately reflects the optimal EE-SE tradeoff relation. We then focus on a special case that priority and fairness are considered and derive an alternative upper bound, which is even proved to be achievable for flat fading channels. We also develop a low-complexity but near-optimal resource allocation algorithm for practical application of EE-SE tradeoff. Numerical results demonstrate that the optimal EE-SE tradeoff relation is a bell shape curve and can be well approached with our resource allocation algorithm.

H.264/AVC adopts many directional spatial prediction models in block-based manner that neighboring pixels on the left and top sides yield prediction for the pixels in a data block to be encoded. However, such models may adapt poorly to the rich textures inside blocks of video signal. In this letter, a new lossless intra coding method based on pixel-wise interleave prediction is presented to enhance the compression performance of H.264/AVC. In our scheme, pixels are coded alternately with interleave prediction, which makes full use of reconstructed pixels to predict later ones in bidirectional or multidirectional manner. Extensive experiments demonstrate that compared to the H.264/AVC standard, our scheme has higher compression ratio, especially for sequences of high resolution. In addition, the scheme can be regarded as a frame-level coding mode and can be easily integrated into the H.264/AVC framework.

Conventional design of wireless networks mainly focuses on system capacity and spectral efficiency (SE). As green radio (GR) becomes an inevitable trend, energy-efficient design is becoming more and more important. In this paper, the fundamental tradeoff between energy efficiency (EE) and SE in downlink orthogonal frequency division multiple access (OFDMA) networks is addressed. We first set up a general EE-SE tradeoff framework, where the overall EE, SE and per-user quality-of-service (QoS) are all considered, and prove that under this framework, EE is strictly quasiconcave in SE. We then discuss some basic properties, such as the impact of channel power gain and circuit power on the EE-SE relation. We also find a tight upper bound and a tight lower bound on the EE-SE curve for general scenarios, which reflect the actual EE-SE relation. We then focus on a special case that priority and fairness are considered and suggest an alternative upper bound, which is proved to be achievable for flat fading channels. We also develop a low-complexity but near-optimal resource allocation algorithm for practical application of the EE-SE tradeoff. Numerical results confirm the theoretical findings and demonstrate the effectiveness of the proposed resource allocation scheme for achieving a flexible and desirable tradeoff between EE and SE.

The fixed-complexity sphere decoder (FSD) has been proposed to attain the near-optimal performance and achieves the same diversity order as the maximum-likelihood decoder (MLD) recently. However, its equally handling all the branches obtained via the full expansion (FE) stages till reaching the final minimum Euclidean distance (MED) decision is unnecessary. In this paper, we conduct an adaptive control of the number of surviving branches for each of the single expansion (SE) stages in the original FSD (AC-FSD). In this controlling method, for each stage, the surviving branches are selected by a threshold value which is calculated from the minimum partial accumulated branch metric and the noise level. We compare the AC-FSD with the original FSD and a recently proposed simplified FSD (SFSD), and simulation results demonstrate that the AC-FSD with proper threshold can attain near-optimal performance with a much lower cost than that of the FSD and the SFSD when the system works in mid and high signal-to-noise ratio (SNR) regimes in practice.

In order to avoid the resource inefficiency of all-participated cooperation in wireless amplify-and-forward relay networks, a novel relay selection scheme based on the channel gain of the source-relay and relay-destination links is proposed. A condition is introduced to maximize the upper bound of the overall received signal-to-noise ratio (SNR). The relay nodes which have bad channel conditions are excluded in turn from the cooperation so that their released resources can be reallocated to other nodes. This paper adopts a simplified power allocation scheme that assumes each selected relay has equal power. The total power is optimally assigned between the source and the relay set. Simulation results show that the proposed scheme can achieve similar BER performance with the scheme which employs all relays and optimal power allocation, but only applies a subset of available relays.

Maximum-likelihood detection (MLD) is the optimal scheme for multiple-input multiple-output (MIMO) channels. However, due to its exponentially high complexity, many alternative algorithms, including some parallel detection (PD) ones with low complexity and high stability, have been proposed for practical applications. Nevertheless, the existing PD algorithms are unable to exploit sufficiently the diversity order increment for low-complexity algorithms via MLD for partial layers, consequently, the complexity of the sub-detectors is still undesirably high. In this paper, a novel PD algorithm with relative low-complexity sub-detectors, i.e., the partial decision feedback sub-detectors, has been developed. Numerical analysis indicates that the proposed parallel algorithm can achieve the near-optimal performance with much lower complexity in comparison with the existing PD algorithms. Thus, this algorithm makes the parallel detection more feasible in real-life systems with limited parallel processing elements.

Maximum-likelihood detection (MLD) is the optimal scheme for vertical Bell Laboratories layered space-time (V-BLAST) systems. However, due to its exponentially high complexity, many alternative algorithms, including some parallel detection (PD) ones with low complexity and high stability, have been proposed instead for practical applications. Nevertheless, the existing PD algorithms are unable to exploit sufficiently the diversity order increment for low-complexity algorithms via exhaustive interference cancellation (EIC) and the complexity of the sub-detectors is still undesirably high. In this paper, a novel PD algorithm with relative low-complexity sub-detectors, i.e., the selective-interference-cancellation sub-detectors, has been developed. The algorithm is abbreviated as PDSIC algorithm. Numerical analysis indicates that the PDSIC algorithm can achieve the near-optimal performance with much lower complexity in comparison with the existing PD algorithms. Thus, the PDSIC algorithm makes the parallel detection more feasible in practical systems with limited parallel processing elements.

The maximum likelihood detection with QR decomposition and M-algorithm (QRM-MLD) has been proposed as a near-optimal multiple-input multiple-output (MIMO) detection scheme which can achieve near maximum likelihood (ML) performance with complexity greatly reduced. However, the performance of the QRM-MLD algorithm will deteriorate with the increasing of the number of transmit antennas, as well as the decreasing of the number of the selected nodes in each stage due to the abandoning of some hypotheses in each step of the tree search. To solve this problem, we modify the QR decomposition method through rearranging the channel columns based on the post-detection signal-to-noise ratio (SNR), which makes the process of the abandoning more reliable. Simulation results show that the new proposed algorithms achieve better performance compared with the conventional QRM-MLD algorithm, especially when the number of transmit antennas is large. Additionally, the increase of the complexity is negligible compared with that of the conventional QRM-MLD algorithm.

In the conventional zero-forcing ordered successive interference cancellation (ZF-OSIC) or minimum mean square error ordered successive interference cancellation (MMSE-OSIC) detection algorithm of vertical Bell-Labs layered space-time (V-BLAST) architecture, there exists an undesirable processing delay due to the calculation of the matrix pseudo-inverse and power reordering in detecting the symbol in each layer. The parallel interference cancellation (PIC) algorithm has a lower processing delay but poorer performance. Based on the features of SIC and PIC algorithms, an integrated PIC and OSIC detection (IPOD) algorithm is proposed which can lower the complexity as well as the processing delay of the whole algorithm with little performance loss. Moreover, there is an alterable parameter in IPOD algorithm which can be changed to obtain different trade off between complexity and performance. Thus, the proposed algorithm is more feasible for practical applications.

We investigate and evaluate the application of the soft information in the detection of cooperative spatial multiplexing (CSM) systems. The destination detects the signals transmitted from the relays with successive interference cancellation (SIC) whose performance suffers from the error propagation. The traditional detection methods assuming that the prior-detected symbols are correct, none of them considers the still existing error propagation. In this paper, we propose a novel soft-information-aided detection algorithm which takes advantage of the log-likelihood ratio (LLR) information of the prior-detected signals. In the proposed algorithm, the interference cancellation and detection ordering both take the error propagation effect into consideration, thus making the detection more reliable. The new algorithm will be performed in the ZF-SIC CSM systems, and the simulation results will show that the new proposed algorithm can achieve better BER performance compared with traditional ones.

OFDM has become one of the most important Beyond-3G transmission technologies. Mobile WiMAX is a typical representative of OFDM systems. The cross-layer optimization problem of inter-cell coordinated resource allocation for OFDM systems is addressed in this paper. We first analyze the problem by utility-based method, and formulate this optimization problem. Then the globally optimal and a sub-optimal inter-cell resource allocation strategy are proposed respectively in multi-cell scenario. Finally, Mobile WiMAX system is taken as an example for evaluation by system level simulation. The results show that the inter-cell resource allocation strategy can achieve better fairness among users in the entire network. Besides, inter-cell adaptive power allocation can enhance the throughput performance while considering the interference of neighbor cells. And the cell-edge throughput gain decreases with the increase of the number of users in one sector.

Maximum-likelihood detection (MLD) can achieve optimum performance for the vertical Bell laboratories layered space-time (V-BLAST) architecture. However, due to its exponentially high computational complexity, several near-optimal detection algorithms, including some parallel detection (PD) ones with low complexity and high stability, have been proposed instead for practical systems. Nevertheless, the existing PD algorithms have a common drawback in equally handling all the branches obtained via exhaustive interference cancellation (EIC) till reaching the final minimum Euclidean distance (MED) decision. In this paper, a simplified PD algorithm, i.e., a generalized parallel interference cancellation (GPIC) algorithm has been developed by means of early termination of the inferior parallel branches. The algorithm is abbreviated as simplified GPIC (SGPIC) algorithm. Numerical analysis indicates that SGPIC algorithm can achieve the near-optimal performance with much lower complexity in comparison with the existing PD algorithms, especially for the cases of high order constellations. Thus, the SGPIC algorithm makes the parallel detection more feasible in practical systems with limited parallel processing elements.